The AI-Powered Healthcare Intelligence Network is an AI-driven system offering disease prediction, drug recommendations, heart disease risk assessment, and an AI medical chatbot. Using ML, NLP, and LLMs, it provides accurate diagnoses, insights, and recommendations, enhancing healthcare accessibility, efficiency, and decision-making .
๐ฉบ AI-Powered Healthcare Intelligence Network
Revolutionizing Healthcare with AI-Driven Predictions, Recommendations, and Insights, Medibot(RAG)
๐ 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.
https://github.com/user-attachments/assets/360876dc-551a-498b-ab75-472137fed751
๐ Features
๐ก Disease Prediction & Medical Recommendation
This module uses Machine Learning to predict diseases based on symptoms and suggest the best medical recommendations.
- โ Predicts diseases based on symptoms provided by the user.
- โ Uses RandomForest Classifier for predictions.
- โ Provides recommended treatments and precautions.
- โ Provides medical descriptions, precautions, medication suggestions, and diet recommendations**.
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๐ AI-Powered Drug Recommendation
Our AI system uses NLP & Cosine Similarity to recommend alternative medicines based on drug properties.
- โ AI-powered alternative medicine finder.
- โ Utilizes NLP & cosine similarity for accurate drug matching
- โ Matches medicines with similar ingredients.
- โ Ensures safer and more effective drug prescriptions.
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๐ช Heart Disease Risk Assessment
This module uses LightGBM & AI classifiers to assess heart disease risks based on patient history.
- โ Evaluates heart disease risk based on lifestyle and medical history.
- โ Uses machine learning models (LightGBM, EasyEnsemble) for predicting heart disease risk.
- โ Takes inputs like age, BMI, smoking habits, medical history, etc.
- โ Provides a personalized heart risk score with AI-driven recommendations
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๐ค Medibot - AI Health Assistant
Our LLM-powered chatbot answers medical queries and provides instant healthcare insights using Hugging Face LLM (Mistral-7B-Instruct).
- โ AI-powered medical chatbot based on Mistral-7B-Instruct.
- โ Retrieves medical information from a FAISS vector database.
- โ Retrieves reliable medical information using RAG (Retrieval Augmented Generation.
- โ Provides fast, relevant, and fact-based healthcare responses.
- โ Provides reliable AI-driven answers to health-related questions.
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๐ Folder Structure
๐ฆ AI-Powered Healthcare Intelligence Network โโโ ๐ models/ # Trained ML models โโโ ๐ data/ # Medical datasets (CSV) โโโ ๐ vectorstore/db_faiss/ # FAISS vector database โโโ ๐ utils/ # Images, styles, and helper files โโโ ๐ pages/ # Individual module pages โโโ ๐ home.py # Main homepage (Streamlit UI) โโโ ๐ requirements.txt # Dependencies โโโ ๐ README.md # Project Documentation โโโ ๐ .gitignore # Ignored files โโโ ๐ styles.css # Custom CSS for UI
โ๏ธ Installation & Setup
1๏ธโฃ Clone the Repository
git clone https://github.com/AbhaySingh71/AI-Powered-Healthcare-Intelligence-System.git cd AI-Powered-Healthcare-Intelligence-System
2๏ธโฃ Set Up the Virtual Environment
python -m venv venv source venv/bin/activate # On macOS/Linux venv\Scripts\activate # On Windows
3๏ธโฃ Install Dependencies
pip install -r requirements.txt
4๏ธโฃ Set Up Environment Variables
Create a .env file and add:
HFTOKEN=yourhuggingfaceapitoken
Ensure it is added to GitHub Secrets when deploying.
5๏ธโฃ Run the Application
streamlit run home.py
๐ Deployment on Streamlit Cloud
1๏ธโฃ Push code to GitHub
git add . git commit -m "Initial commit" git push origin main
2๏ธโฃ Deploy on Streamlit
- Go to Streamlit Cloud โ Deploy a new app.
- Set
HF_TOKENin Streamlit Secrets. - Click Deploy! ๐
โ๏ธ 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
๐ Why Use This App?
- ๐ฅ AI-Powered Healthcare Insights: Get data-driven medical predictions.
- โ๏ธ Enhances Patient Care: Supports doctors and patients in making informed decisions.
- ๐ก Real-Time Recommendations: Provides immediate AI-assisted insights.
- โณ Saves Time: Automates diagnosis and medical recommendations.
- ๐ฌ Empowers Medical Research: Helps in early disease detection and prevention.
Docker Deployment
This project is Docker-first. Docker ensures that the model can run in any environment without worrying about Python versions, dependencies, or system settings.
docker pull abhaysingh71/ai-powered-healthcare-system
docker run -p 8501:8501 abhaysingh71/ai-powered-healthcare-system
โ Why Docker?
- Environment-independent deployments
- Fast setup and teardown
- Easy to host on cloud (AWS, GCP, Azure)
- Reproducibility for teams and CI/CD pipelines
๐ Docker hub
๐ License
This project is licensed under the MIT License. Feel free to use, modify, and contribute!
๐ฌ Contact Us
Have questions or need support? Reach out to us at: