https://github.com/carlpecardal/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/carlpecardal/lung_cancer_prediction
algorithm-analysis classification computational-pathology data-analysis decision-tree-classifier gradientboosting histopathology keras logistic-regression lung-cancer multiple-instance-learning svm tissue-microarray-analysis 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/carlpecardal/lung_cancer_prediction
- Owner: carlpecardal
- License: mit
- Created: 2025-03-25T21:36:56.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2025-03-25T22:31:12.000Z (about 2 months ago)
- Last Synced: 2025-03-25T22:33:15.855Z (about 2 months ago)
- Topics: algorithm-analysis, classification, computational-pathology, data-analysis, decision-tree-classifier, gradientboosting, histopathology, keras, logistic-regression, lung-cancer, multiple-instance-learning, svm, tissue-microarray-analysis, xgboost
- Language: Jupyter Notebook
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0