🧠 CareRisk AI

Intelligent Healthcare Risk Prediction using Machine Learning

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🌍 Overview

CareRisk AI predicts whether a healthcare client is Low, Medium, or High Risk using Machine Learning.

It combines data preprocessing, feature engineering, model training, evaluation, and an interactive dashboard into one complete application.

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🚀 Features

✨ Machine Learning Pipeline

📊 Exploratory Data Analysis

🧹 Data Cleaning

⚙ Feature Engineering

🌲 Random Forest

📈 Logistic Regression

🧠 Support Vector Machine

📉 XGBoost

📊 Model Comparison

🎯 Risk Prediction

🌐 Streamlit Dashboard

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🏗 System Architecture

Patient Records
       │
       ▼
 Data Cleaning
       │
       ▼
 Feature Engineering
       │
       ▼
 Machine Learning Models
       │
       ▼
 Prediction Engine
       │
       ▼
 Interactive Dashboard

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💻 Tech Stack

Technology	Usage
🐍 Python	Machine Learning
📊 Pandas	Data Analysis
🔢 NumPy	Numerical Computing
🤖 Scikit-Learn	ML Models
📈 Matplotlib	Visualization
🌐 Streamlit	Web App

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📁 Project Structure

📦 care-risk-prediction-ml
 ┣ 📂 app
 ┣ 📂 data
 ┣ 📂 models
 ┣ 📂 notebooks
 ┣ 📂 reports
 ┣ 📂 screenshots
 ┣ 📂 src
 ┣ 📂 tests
 ┣ 📜 requirements.txt
 ┣ 📜 README.md
 ┗ 📜 LICENSE

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📸 Preview

Dashboard	Prediction
Coming Soon	Coming Soon

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📈 Model Performance

✔ Accuracy

✔ Precision

✔ Recall

✔ F1 Score

✔ ROC Curve

✔ Confusion Matrix

✔ Feature Importance

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⚡ Installation

git clone https://github.com/tasnem-tech/care-risk-prediction-ml.git

cd care-risk-prediction-ml

pip install -r requirements.txt

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▶ Run

python src/train.py

streamlit run app/streamlit_app.py

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🔮 Future Improvements

• 🤖 Deep Learning
• 📡 REST API
• ☁ Cloud Deployment
• 📱 Mobile Application
• 🧠 SHAP Explainability
• 🐳 Docker Support

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👨‍💻 Tasnem Islam Prome

Machine Learning • Data Analytics • Python Development

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