https://github.com/mafrs47/lung_cancer_prediction
This project predicts lung cancer risks using machine learning models like Random Forest, Logistic Regression, and SVM. It analyzes patient data with features such as age, smoking habits, and symptoms. Data preprocessing, visualization, and performance evaluation ensure accurate predictions for early diagnosis.
https://github.com/mafrs47/lung_cancer_prediction
cnn computational-pathology convolutional-neural-networks decision-tree-classifier decision-trees deep-learning gradientboosting histopathology jupyter-notebook lung-cancer multiple-instance-learning scikit-learn svm xgboost
Last synced: about 2 months ago
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This project predicts lung cancer risks using machine learning models like Random Forest, Logistic Regression, and SVM. It analyzes patient data with features such as age, smoking habits, and symptoms. Data preprocessing, visualization, and performance evaluation ensure accurate predictions for early diagnosis.
- Host: GitHub
- URL: https://github.com/mafrs47/lung_cancer_prediction
- Owner: mafrs47
- License: mit
- Created: 2025-03-25T22:11:45.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2025-03-25T23:09:28.000Z (about 2 months ago)
- Last Synced: 2025-03-25T23:28:43.014Z (about 2 months ago)
- Topics: cnn, computational-pathology, convolutional-neural-networks, decision-tree-classifier, decision-trees, deep-learning, gradientboosting, histopathology, jupyter-notebook, lung-cancer, multiple-instance-learning, scikit-learn, svm, xgboost
- Language: Jupyter Notebook
- Size: 1.36 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0