In the world of preventive healthcare, data-driven insights can empower people to make better lifestyle decisions. That's why I built an AI-powered Health Assessment Chatbot that not only asks meaningful health-related questions but also generates detailed, personalized health analysis reports — all through a friendly and interactive web interface.
🚀 What I Built
The Health Assessment Chatbot is a smart application that:
Interactively asks health and lifestyle questions.
Performs real-time calculations and health evaluations.
Uses Generative AI to provide tailored recommendations.
Generates a comprehensive health report based on your responses.
Here’s a snapshot from a sample report it produces:
📊 Sample Health Summary
Overall Health Score: 76 / 100
Moderate risk: Good health with room for improvement.
Key Metrics:
BMI: 24.9 (Normal)
Waist-to-Height Ratio (WHTR): 0.471 (Good)
Resting Metabolic Rate: 1926 kcal/day
Daily Calorie Goal: 2312 kcal
Category Breakdown:
✅ Body Profile: 95/100
⚠ Lifestyle: 79/100
⚠ Stress Management: 63.3/100
❌ Exercise: 20/100
✅ Hydration: 90/100
Hydration Reminder: Drink ~12 glasses/day (current: 2750ml)
Personalized Tips: AI-generated suggestions for diet, exercise, and stress.
🧰 Tech Stack
This project combines the power of data science and modern web tools:
Python 🐍 – Core logic, health metric calculations.
Streamlit 🌐 – Quick and beautiful UI for interaction.
Generative AI 🧠 – Provides intelligent analysis and custom recommendations.
Pandas – For data wrangling.
NumPy – For numerical operations.
💡 Key Features
🤖 Conversational UI: Feels like talking to a health assistant.
📈 Real-time Health Metrics: BMI, WHTR, BMR, hydration, calorie needs, and more.
📋 AI Recommendations: Diet, exercise, sleep, and stress management tips.
📤 Exportable Report: Users can save or share their health reports.
🔁 Assessment Retake: Restart the chat anytime to update data.
🔍 How It Works
User answers health questions → Age, weight, diet, activity, hydration, sleep, etc.
AI and Python backend calculates:
BMI, WHTR, Metabolic Rate
Daily calorie needs
Hydration percentage
LLM generates recommendations for improvement.
Streamlit renders a beautiful report with charts and metrics.
🎯 Future Plans
📱 Mobile responsiveness and deployment to the cloud.
🩺 Doctor-mode integration for medical professionals.
🧬 Adding more complex indicators like blood sugar, lipid profile, etc.
📚 Long-term trend analysis with user accounts.
🙌 Final Thoughts
Healthcare shouldn't be reactive. With AI and data, we can make it proactive. This project is just a small step in that direction — helping people understand and improve their health through meaningful interaction and actionable insights.
Let me know your thoughts, suggestions, or ideas to improve this further! 💬
Top comments (3)
Love the level of actionable insight this gives! Any plans to let users integrate their own health data from wearables or export results to other apps?
That sounds amazing! Going for personalized health care is a great way to track ourselves and manage our health. Cool! AI is making our lives manageable.
This is amazing.