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.

25
/ 100
Experimental

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.

cancer-risk-assessment preventive-care public-health epidemiology medical-screening
No Package No Dependents
Maintenance 10 / 25
Adoption 4 / 25
Maturity 11 / 25
Community 0 / 25

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Stars

7

Forks

Language

License

MIT

Last pushed

Jan 27, 2026

Commits (30d)

0

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