ML-Healthcare-Web-App and Heart-Disease

These two tools are competitors because both offer Streamlit web applications for disease risk assessment, with A providing a broader range of machine learning algorithms for multi-disease prediction, while B focuses specifically on heart disease prediction.

ML-Healthcare-Web-App
42
Emerging
Heart-Disease
27
Experimental
Maintenance 0/25
Adoption 8/25
Maturity 16/25
Community 18/25
Maintenance 0/25
Adoption 4/25
Maturity 9/25
Community 14/25
Stars: 45
Forks: 13
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
Stars: 8
Forks: 3
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About ML-Healthcare-Web-App

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.

About Heart-Disease

Prem07a/Heart-Disease

"Coding a Streamlit web app for heart disease prediction using a trained machine learning model."

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