Skip to content

BafokengMasitha/Health-Advisor-Bot

 
 

Repository files navigation

Health-Advisor-Bot

Health Advisor Bot is an AI-powered diagnostic system using TF-IDF/cosine similarity to match symptoms with conditions. It provides medicine, herbal, nutrition & lifestyle recommendations. Demonstrates genAI understanding through intelligent corpus construction & multi-modal responses for African healthcare contexts.

🩺 Health Advisor Bot

An AI-powered health advisory system that provides symptom-based health recommendations using machine learning and comprehensive medical datasets. Built for the African context with support for conventional medicine, herbal treatments, and nutritional advice.

🌟 Features

  • Symptom-Based Diagnosis: Input symptoms and receive potential condition matches
  • Multi-Modal Recommendations:
    • 💊 Conventional medicine suggestions
    • 🌿 Herbal and traditional remedies
    • 🍎 Nutritional and dietary advice
    • ❤️ Lifestyle recommendations

run jupyternotebook run_advisor_interactive()

web interface Prerequisites

  • Python 3.8+
  • pip package manager

Installation

  1. Clone the repository
    git clone <repository-url>
    cd health-advisor
    
  2. Install dependencies

pip install pandas scikit-learn flask

Add your datasets (place in project root):

symptoms.csv - Primary symptom-disease mappings

observations.csv - Clinical observations and causes

conditions.csv - Medical conditions database

careplans.csv - Treatment plans and recommendations

medicine_disease.csv - Medicine recommendations

herbaltreatment_disease.csv - Herbal remedies

nutrition_disease.csv - Nutritional advice

allergies.csv - Allergy information

Run the application python app.py

Access the web interface Open http://localhost:5000 in your browser

About

Health Advisor Bot is an AI-powered diagnostic system using TF-IDF/cosine similarity to match symptoms with conditions. It provides medicine, herbal, nutrition & lifestyle recommendations. Demonstrates genAI understanding through intelligent corpus construction & multi-modal responses for African healthcare contexts.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages

  • Jupyter Notebook 55.7%
  • Python 34.4%
  • HTML 9.9%