🩺 AI-Powered Healthcare Intelligence Network

Revolutionizing Healthcare with AI-Driven Predictions, Recommendations, and Insights, Medibot(RAG)

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📌 About This Project

The AI-Powered Healthcare Intelligence Network is a cutting-edge platform that leverages Machine Learning (ML) and Natural Language Processing (NLP) to provide accurate disease predictions, personalized medical recommendations, and AI-assisted drug suggestions. The system aims to enhance early diagnosis, reduce medical errors, and offer intelligent healthcare solutions.

AI.Powered.Healthcare.System.3.mp4

🚀 Features

💡 Disease Prediction & Medical Recommendation

This module uses Machine Learning to predict diseases based on symptoms and suggest the best medical recommendations.

• ✅ Predicts diseases based on symptoms provided by the user.
• ✅ Uses RandomForest Classifier for predictions.
• ✅ Provides recommended treatments and precautions.
• ✅ Provides medical descriptions, precautions, medication suggestions, and diet recommendations**.

💊 AI-Powered Drug Recommendation

Our AI system uses NLP & Cosine Similarity to recommend alternative medicines based on drug properties.

• ✅ AI-powered alternative medicine finder.
• ✅Utilizes **NLP & cosine similarity** for **accurate drug matching**
• ✅ Matches medicines with similar ingredients.
• ✅ Ensures safer and more effective drug prescriptions.

🪀 Heart Disease Risk Assessment

This module uses LightGBM & AI classifiers to assess heart disease risks based on patient history.

• ✅ Evaluates heart disease risk based on lifestyle and medical history.
• ✅ Uses machine learning models (LightGBM, EasyEnsemble) for predicting heart disease risk.
• ✅ Takes inputs like age, BMI, smoking habits, medical history, etc.
• ✅ Provides a **personalized heart risk score with AI-driven recommendations**

🤖 Medibot - AI Health Assistant

Our LLM-powered chatbot answers medical queries and provides instant healthcare insights using Hugging Face LLM (Mistral-7B-Instruct).

• ✅ AI-powered medical chatbot based on Mistral-7B-Instruct.
• ✅ Retrieves medical information from a FAISS vector database.
• ✅ Retrieves reliable medical information using RAG (Retrieval Augmented Generation.
• ✅ Provides fast, relevant, and fact-based healthcare responses.
• ✅ Provides reliable AI-driven answers to health-related questions.

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📂 Folder Structure

📦 AI-Powered Healthcare Intelligence Network
│── 📂 models/                         # Trained ML models
│── 📂 data/                           # Medical datasets (CSV)
│── 📂 vectorstore/db_faiss/           # FAISS vector database
│── 📂 utils/                          # Images, styles, and helper files
│── 📂 pages/                          # Individual module pages
│── 📜 home.py                         # Main homepage (Streamlit UI)
│── 📜 requirements.txt                 # Dependencies
│── 📜 README.md                        # Project Documentation
│── 📜 .gitignore                        # Ignored files
│── 📜 styles.css                        # Custom CSS for UI

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⚙️ Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/mimi-netizen/Healthcare-AI-System.git
cd Healthcare-Intelligence-System

2️⃣ Set Up the Virtual Environment

python -m venv venv
source venv/bin/activate  # On macOS/Linux
venv\Scripts\activate  # On Windows

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Set Up Environment Variables

Create a .env file and add:

HF_TOKEN=your_huggingface_api_token

Ensure it is added to GitHub Secrets when deploying.

5️⃣ Run the Application

streamlit run home.py

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🚀 Deployment on Streamlit Cloud

1️⃣ Push code to GitHub

git add .
git commit -m "Initial commit"
git push origin main

2️⃣ Deploy on Streamlit

• Go to Streamlit Cloud → Deploy a new app.
• Set HF_TOKEN in Streamlit Secrets.
• Click Deploy! 🎉

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⚙️ Technologies Used

• Machine Learning: RandomForest, LightGBM, NLP, Cosine Similarity
• AI & NLP: Hugging Face Transformers, LangChain, FAISS
• Data Handling: Pandas, NumPy, Pickle
• Web Framework: Streamlit
• Visualization: Plotly, SHAP for feature importance
• Cloud Deployment: AWS, GCP

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🔍 Why Use This App?

• 🏥 AI-Powered Healthcare Insights: Get data-driven medical predictions.
• ⚕️ Enhances Patient Care: Supports doctors and patients in making informed decisions.
• 💡 Real-Time Recommendations: Provides immediate AI-assisted insights.
• ⏳ Saves Time: Automates diagnosis and medical recommendations.
• 🔬 Empowers Medical Research: Helps in early disease detection and prevention.

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📜 License

This project is licensed under the MIT License. Feel free to use, modify, and contribute!

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📬 Contact Us

Have questions or need support? Reach out to us at:

• 📧 [email protected]

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🌐 Connect With Me

🔗 LinkedIn