https://github.com/harphies/aimodels.ai
AI models
https://github.com/harphies/aimodels.ai
Last synced: 12 months ago
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AI models
- Host: GitHub
- URL: https://github.com/harphies/aimodels.ai
- Owner: Harphies
- Created: 2020-05-28T08:52:09.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2022-09-30T20:03:54.000Z (over 3 years ago)
- Last Synced: 2023-03-05T14:08:01.934Z (over 3 years ago)
- Language: Python
- Size: 14.6 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 5
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Metadata Files:
- Readme: README.md
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README
## Building explanaible AI models for medical applications.
### _Anyone— patients, doctor, organization, medical IoT device developer, or researcher— can access in order to make more informed clinical decisions._
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We focus more on leveraging pretrained models and architecture and less attention on custom training at the early stage
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- computer vision for medical diagnosis: Computer-aided disease diagnosis. (object detection, image classification, Image segmentation, image tagging, image similarity)
- Systems for diabetics Retinopathy(Segmentation, Grading and Localization) based on an image of the human eye: A system which based on an image of human eye classifies Diabetic Retinopathy disease using image processing and machine learning methods
- Morphological image processing methods are used to extract features like exudates and red lesion which characterise the disease.
- XGBoost and other models are used to classify disease into five categories.
- A Django/flask WebApp for demo
- U-Net architecture for segmentation of lesions, and a ResNet model for disease grading.
- Scanning medical images for abnormalities.
- Cancer diagnosis (Breast cancer etc)
- Diagnosing heart diseases.
- Tumor detection
- Alzheimer's and parkinson's Detection
- Brain Injuries
- Internal bleeding
- Pneumonia
- Medical Images and EHR (X-ray, ultrasound, CT or MRI scan) for diagnosing varieties of diseases.
- sourcing training and testing data for medical applications
- Recommendation systems for personalized treatments
- Using Artificial Intelligence to make dental treatments more efficient, affordable and personalized.
- Precise cancer diagnosis and personalized treatment decisions.
## Demos
- [Click here to the documentation](https://aimodels.herokuapp.com/apidocs/)
- [Test on Postman here](https://aimodels.herokuapp.com)
## API's
- [Diabetics Retinopathy]()