mdzaheerjk/Predictive-Modeling-for-Cancer-Risk-Assessment-Using-MachineLearning
This project develops a machine learning model to predict cancer risk levels (High, Medium, Low) based on demographic, behavioral, and health data. It addresses class imbalance using techniques like SMOTE and optimizes model performance with hyperparameter tuning, providing crucial insights for early detection and intervention.
This project helps medical professionals and public health researchers identify individuals at different levels of cancer risk. By inputting demographic, behavioral, and health data, it outputs predictions of whether a person's cancer risk is High, Medium, or Low. This tool is designed for healthcare providers, epidemiologists, and public health officials looking to enhance early detection and targeted intervention strategies.
Use this if you need to quickly assess an individual's potential cancer risk based on a range of personal health and lifestyle factors.
Not ideal if you require a diagnostic tool for definitive cancer diagnosis rather than a risk prediction.
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MIT
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Last pushed
Jan 27, 2026
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