advikmaniar/ML-Healthcare-Web-App

This is a Machine Learning web app developed using Python and StreamLit. Uses algorithms like Logistic Regression, KNN, SVM, Random Forest, Gradient Boosting, and XGBoost to build powerful and accurate models to predict the status of the user (High Risk / Low Risk) with respect to Heart Attack and Breast Cancer.

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Emerging

This application helps healthcare professionals or medical students explore how different machine learning models can predict health risks. You input patient attributes like age, sex, and heart rate, and the system outputs a 'High Risk' or 'Low Risk' prediction for heart attack or breast cancer. It's designed for those who want to understand predictive modeling in healthcare.

No commits in the last 6 months.

Use this if you want to interactively build and test machine learning models for heart attack or breast cancer risk prediction, and understand how different algorithms and their parameters influence the outcomes.

Not ideal if you are looking for a clinical diagnostic tool or a system for real-world patient data analysis beyond exploring model capabilities.

predictive-health medical-risk-assessment healthcare-education machine-learning-exploration disease-prediction
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 18 / 25

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Stars

45

Forks

13

Language

Python

License

Apache-2.0

Last pushed

Nov 16, 2021

Commits (30d)

0

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