awesome-pain-intensity-classification-papers
A comprehensive list of pain intensity classification papers mainly based on deep learning algorithms
https://github.com/zhenyuanlu/awesome-pain-intensity-classification-papers
Last synced: about 12 hours ago
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Latest Review/Survey papers
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Review and Analysis of Pain Research Literature through Keyword Co-occurrence Networks
- Pain and Stress Detection Using Wearable Sensors and Devices—A Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Sensor Technologies to Manage the Physiological Traits of Chronic Pain: A Review
- Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review
- Automatic Recognition Methods Supporting Pain Assessment: A Survey
- A Review of Automated Pain Assessment in Infants: Features, Classification Tasks, and Databases
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- A Review of Automated Pain Assessment in Infants: Features, Classification Tasks, and Databases
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
- Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
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Pain Classification Papers
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Objective Measurement of Subjective Pain Perception with Autonomic Body Reactions in Healthy Subjects and Chronic Back Pain Patients: An Experimental Heat Pain Study
- Explainable Artificial Intelligence (XAI) in Pain Research: Understanding the Role of Electrodermal Activity for Automated Pain Recognition
- Transformer Encoder with Multiscale Deep Learning for Pain Classification Using Physiological Signals
- Personalized Deep Bi-LSTM RNN Based Model for Pain Intensity Classification Using EDA Signal
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Multi-Modal Pain Intensity Assessment Based on Physiological Signals: A Deep Learning Perspective - supervised Learning, Auto-Encoder | EMG + ECG + EDA | BioVid; SenseEmotion |
- Automated Nociceptive Pain Assessment Using Physiological Signals and a Hybrid Deep Learning Network - time Data |
- Comparison of Feature Extraction Methods for Physiological Signals for Heat-Based Pain Recognition
- Pain Recognition With Electrocardiographic Features in Postoperative Patients: Method Validation Study
- Exploration of physiological sensors, features, and machine learning models for pain intensity estimation
- Objective Pain Assessment Using Wrist-based PPG Signals: A Respiratory Rate Based Method
- Machine learning suggests sleep as a core factor in chronic pain - Sources Parametes | Proprietary Dataset: chronic pain, Finland|
- Assessment of thoracic pain using machine learning: a case study from Baja California, Mexico
- Prediction of breakthrough pain during labour neuraxial analgesia: comparison of machine learning and multivariable regression approaches
- Hybrid RNN-ANN Based Deep Physiological Network for Pain Recognition
- Pain phenotypes classified by machine learning using electroencephalography features
- Machine-learning-based knowledge discovery in rheumatoid arthritis-related registry data to identify predictors of persistent pain - sources Parameters | Proprietary Dataset: Rheumatoid arthritis |
- Diverse frequency band-based convolutional neural networks for tonic cold pain assessment using EEG
- Using a motion sensor to categorize nonspecific low back pain patients: a machine learning approach
- Identifying predictive factors for neuropathic pain after breast cancer surgery using machine learning - and-health-professions/prospective-cohort-study), Neuropathic pain|
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Feature extraction and selection for pain recognition using peripheral physiological signals
- Predicting inadequate postoperative pain management in depressed patients: a machine learning approach
- Exploring Deep Physiological Models for Nociceptive Pain Recognition
- A Deep Neural Network-Based Pain Classifier Using a Photoplethysmography Signal - /Post-operation of Surgery |
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Machine learning-based prediction of clinical pain using multimodal neuroimaging and autonomic metrics
- A joint deep neural network model for pain recognition from face - McMaster Shoulder Pain |
- Deep Multimodal Pain Recognition: A Database and Comparison of Spatio-Temporal Visual Modalities
- Continuous Pain Intensity Estimation from Autonomic Signals with Recurrent Neural Networks - NN| EDA, HR | BioVid
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Improving pain management in patients with sickle cell disease from physiological measures using machine learning techniques
- Prediction effects of personal, psychosocial, and occupational risk factors on low back pain severity using artificial neural networks approach in industrial workers
- Multi-task neural networks for personalized pain recognition from physiological signals
- Physiological Signal-Based Method for Measurement of Pain Intensity
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Automatic Pain Recognition from Video and Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Tree-Based Models for Pain Detection from Biomedical Signals
- Multi-Modal Pain Intensity Assessment Based on Physiological Signals: A Deep Learning Perspective - supervised Learning, Auto-Encoder | EMG + ECG + EDA | BioVid; SenseEmotion |
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Identifying predictive factors for neuropathic pain after breast cancer surgery using machine learning - and-health-professions/prospective-cohort-study), Neuropathic pain|
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Transformer Encoder with Multiscale Deep Learning for Pain Classification Using Physiological Signals
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Continuous Pain Intensity Estimation from Autonomic Signals with Recurrent Neural Networks - NN| EDA, HR | BioVid
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Prediction of breakthrough pain during labour neuraxial analgesia: comparison of machine learning and multivariable regression approaches
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Improving pain management in patients with sickle cell disease from physiological measures using machine learning techniques
- Prediction effects of personal, psychosocial, and occupational risk factors on low back pain severity using artificial neural networks approach in industrial workers
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Diverse frequency band-based convolutional neural networks for tonic cold pain assessment using EEG
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Tree-Based Models for Pain Detection from Biomedical Signals
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Classification of Heat-Induced Pain Using Physiological Signals - pain data
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Tree-Based Models for Pain Detection from Biomedical Signals
- Machine learning suggests sleep as a core factor in chronic pain - Sources Parametes | Proprietary Dataset: chronic pain, Finland|
- Machine-learning-based knowledge discovery in rheumatoid arthritis-related registry data to identify predictors of persistent pain - sources Parameters | Proprietary Dataset: Rheumatoid arthritis |
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Machine learning suggests sleep as a core factor in chronic pain - Sources Parametes | Proprietary Dataset: chronic pain, Finland|
- Machine-learning-based knowledge discovery in rheumatoid arthritis-related registry data to identify predictors of persistent pain - sources Parameters | Proprietary Dataset: Rheumatoid arthritis |
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Tree-Based Models for Pain Detection from Biomedical Signals
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Machine learning suggests sleep as a core factor in chronic pain - Sources Parametes | Proprietary Dataset: chronic pain, Finland|
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Tree-Based Models for Pain Detection from Biomedical Signals
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Tree-Based Models for Pain Detection from Biomedical Signals
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
- Tree-Based Models for Pain Detection from Biomedical Signals
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Tree-Based Models for Pain Detection from Biomedical Signals
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
- Tree-Based Models for Pain Detection from Biomedical Signals
- Interpretable machine learning models for classifying low back pain status using functional physiological variables
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Feature extraction and selection for pain recognition using peripheral physiological signals
- Acute pain intensity monitoring with the classification of multiple physiological parameters
- Deep learning model for detection of pain intensity from facial expression - CNN-VSL-CRF | Facial Expressions | - |
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