🏥 SymptoGuide

AI-Powered Healthcare Assistant for Symptom Analysis & Medical Guidance

SymptoGuide is an intelligent healthcare assistance system that helps users understand and categorize their symptoms, providing preliminary assessments and guiding them toward appropriate medical experts or hospitals.

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🎯 Problem Statement

Community Connection Challenge - The Local Services Trust Problem

Develop an intelligent healthcare assistance system that:

• ✅ Helps users understand and categorize their symptoms
• ✅ Provides preliminary, non-diagnostic assessments
• ✅ Guides users toward appropriate medical experts or hospitals
• ✅ Identifies emergency indicators and concern areas
• ✅ Recommends departments and specialists

⚠️ Disclaimer: This system does NOT replace professional medical diagnosis. Always consult a healthcare provider for medical advice.

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💡 Our Solution

SymptoGuide combines Machine Learning and Natural Language Processing to:

1. 🗣️ Accept natural language symptom descriptions - "I have a bad headache and feeling very tired"
2. 🔍 Extract and identify symptoms using NLP with 100+ phrase mappings
3. 🤖 Predict potential conditions using an ensemble ML model (Random Forest + Gradient Boosting + SVM)
4. 📊 Assess severity levels and identify emergency indicators
5. 💊 Provide recommendations including specialists, medications, diet, and precautions
6. 🏥 Connect users to nearby hospitals and appropriate departments

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✨ Features

🔬 AI-Powered Symptom Analysis

• Natural language processing for symptom extraction
• Support for 230+ medical symptoms
• Intelligent phrase matching ("chest pain", "difficulty breathing", etc.)

🎯 Disease Prediction

• Ensemble machine learning model with 95%+ accuracy
• Top-3 disease predictions with confidence scores
• Confidence level indicators (High/Medium/Low)

🚨 Emergency Detection

• Automatic identification of red-flag symptoms
• Emergency severity scoring
• Urgent care recommendations

👨‍⚕️ Smart Recommendations

• Specialist recommendations based on predicted condition
• Personalized precautions and medications
• Diet and workout suggestions
• Nearby hospital finder

💻 Modern User Interface

• Step-by-step symptom checker wizard
• Real-time symptom extraction preview
• Beautiful, responsive design
• Dark/Light mode support

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🛠️ Tech Stack

Frontend

Technology	Purpose
⚛️ React 18	UI Framework
📘 TypeScript	Type Safety
⚡ Vite	Build Tool
🎨 Tailwind CSS	Styling
🧩 Shadcn/UI	Component Library
🔄 React Query	Data Fetching
🧭 React Router	Navigation
📊 Recharts	Data Visualization

Backend

Technology	Purpose
🐍 Python 3.10+	Core Language
🌐 Flask	REST API Framework
🤖 Scikit-learn	Machine Learning
🔢 Pandas & NumPy	Data Processing
📝 NLTK	Natural Language Processing
📦 Pickle	Model Serialization

Machine Learning Model

Component	Details
🎲 Algorithm	Ensemble (Random Forest + Extra Trees + Gradient Boosting + KNN + SVM)
📊 Features	230 binary symptom features
🏷️ Classes	40+ disease categories
📈 Accuracy	95%+ on test data

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📁 Project Structure

SymptoGuide/
├── 📂 backend/
│   ├── 📄 app.py                    # Flask API server
│   ├── 📄 requirements.txt          # Python dependencies
│   ├── 📦 healthcare_model.pkl      # Trained ML model
│   ├── 📂 data/
│   │   ├── 📂 cleaned_datasets/     # Processed data files
│   │   │   ├── diseases_symptoms_cleaned.csv
│   │   │   ├── symptom_severity_cleaned.csv
│   │   │   ├── medications_cleaned.csv
│   │   │   ├── precautions_cleaned.csv
│   │   │   ├── diets_cleaned.csv
│   │   │   └── ...
│   │   └── 📂 raw_data/             # Original datasets
│   └── 📂 model/
│       ├── 📄 Healthcare_Assistant_System.py  # Core ML model
│       ├── 📄 Interract.py                    # CLI & NLP extraction
│       ├── 📄 Feature_Engineering.py          # Feature processing
│       └── 📄 Complete_data_clean.py          # Data preprocessing
│
├── 📂 frontend/
│   ├── 📄 package.json              # Node dependencies
│   ├── 📄 vite.config.ts            # Vite configuration
│   ├── 📄 tailwind.config.ts        # Tailwind CSS config
│   └── 📂 src/
│       ├── 📄 App.tsx               # Main App component
│       ├── 📂 pages/
│       │   ├── 📄 Index.tsx         # Landing page
│       │   ├── 📄 SymptomChecker.tsx # Symptom input wizard
│       │   ├── 📄 Results.tsx       # Analysis results
│       │   ├── 📄 Hospitals.tsx     # Hospital finder
│       │   └── 📄 Specialists.tsx   # Specialist directory
│       ├── 📂 components/           # Reusable UI components
│       ├── 📂 services/
│       │   └── 📄 api.ts            # Backend API client
│       └── 📂 data/
│           └── 📄 mockData.ts       # Fallback data
│
├── 📄 README.md
├── 📄 LICENSE
└── 📄 package.json

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🚀 Getting Started

Prerequisites

Requirement	Version
🐍 Python	3.10+
📦 Node.js	18+
📦 npm/bun	Latest

Installation

1️⃣ Clone the Repository

git clone https://github.com/ParthShikhare19/SymptoGuide.git
cd SymptoGuide

2️⃣ Backend Setup

cd backend

# Create virtual environment (recommended)
python -m venv venv
venv\Scripts\activate  # Windows
# source venv/bin/activate  # Linux/Mac

# Install dependencies
pip install -r requirements.txt

# Download NLTK data (first time only)
python -c "import nltk; nltk.download('punkt'); nltk.download('stopwords'); nltk.download('wordnet')"

3️⃣ Frontend Setup

cd frontend

# Install dependencies
npm install
# or
bun install

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▶️ Running the Application

Start Backend Server

cd backend
python app.py

The API will be available at http://localhost:5000

Start Frontend Development Server

cd frontend
npm run dev
# or
bun dev

The app will be available at http://localhost:5173

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🔌 API Endpoints

Method	Endpoint	Description
GET	/api/health	Health check
GET	/api/symptoms	Get all available symptoms
GET	/api/symptom-keywords	Get symptom keywords for NLP
POST	/api/analyze	Analyze symptoms (ML-powered)
POST	/api/assess	Simple triage assessment
POST	/api/extract-symptoms	Extract symptoms from text

Example: Analyze Symptoms

curl -X POST http://localhost:5000/api/analyze \
  -H "Content-Type: application/json" \
  -d '{
    "symptoms": ["fever", "headache", "fatigue"],
    "description": "I have been feeling very tired with high fever",
    "severity": "moderate",
    "duration": "3-7 days"
  }'

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🧪 Testing the Model (CLI)

You can test the model directly from the command line:

cd backend/model
python Interract.py

Then enter symptoms naturally:

🗣️  Describe how you're feeling: I have a bad headache, fever and feeling very tired

✅ Identified 3 symptom(s):
   1. Headache
   2. High Fever
   3. Fatigue

Predicted Disease: Typhoid
Confidence: 87.3%
Recommended Specialist: Infectious Disease Specialist

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📊 Datasets Used

Dataset	Description	Records
diseases_symptoms_cleaned.csv	Disease-symptom mappings	4,920
symptom_severity_cleaned.csv	Symptom severity weights	133
disease_description_cleaned.csv	Disease descriptions	41
precautions_cleaned.csv	Disease precautions	41
medications_cleaned.csv	Recommended medications	41
diets_cleaned.csv	Diet recommendations	41
workouts_cleaned.csv	Workout recommendations	41

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🔮 Future Enhancements

• 🌐 Multi-language support
• 📱 Mobile app (React Native)
• 🗺️ Real-time hospital mapping with Google Maps API
• 📞 Telemedicine integration
• 📈 User health history tracking
• 🔔 Symptom progression alerts

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📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

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👥 Contributors

Chetan Chaudhari

Nischay Chavan

Parth Shikhare

Tanvi Patil

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Made with ❤️ for better healthcare accessibility

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