🩺 Healthcare Predictive Analytics

This project focuses on applying Machine Learning models for predictive healthcare analytics.
The goal is to assist in early diagnosis and risk prediction using structured medical datasets.

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🎯 Problem Statement

Healthcare providers face challenges in predicting diseases early due to:

• Large volumes of patient data
• Noisy & imbalanced datasets
• The need for interpretable predictions

This project applies ML models to predict outcomes, compare performance, and generate visual + PDF reports for decision support.

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📊 Dataset

• Source: Public healthcare dataset (e.g., Pima Indians Diabetes Dataset)
• Features: Patient health attributes (glucose, BMI, blood pressure, etc.)
• Target: Binary classification (disease present / not present)

⚙️ How to Run

1. Clone the repo:

   git clone  https://github.com/akshataundri/healthcare-predictive-analytics.git
   cd healthcare-predictive-analytics

2. Create environment & install dependencies:

   python -m venv venv source venv/bin/activate # Linux/Mac venv\Scripts\activate # Windows pip install -r requirements.txt

3. Run training:

   python src/train.py

4. Generate evaluation report:

   python src/evaluate.py

🚀 Future Work

Hyperparameter tuning

Integration with real-time healthcare systems

Deployment as an API for hospitals/clinics

Explainable AI (feature importance, SHAP values)