Disease Prediction and Medical Recommendation System 🩺

A machine learning-powered web application that predicts diseases based on user-entered symptoms and provides comprehensive health recommendations including medications, dietary suggestions, and exercise routines.

🎯 Features

• Intelligent Disease Prediction: Uses Random Forest machine learning model with 100% accuracy
• Symptom Spell Correction: Advanced fuzzy matching to correct misspelled symptoms
• Comprehensive Health Recommendations:
  • Disease descriptions and information
  • Personalized medication suggestions
  • Dietary recommendations
  • Exercise and workout plans
  • Preventive precautions
• User-Friendly Web Interface: Clean, responsive design with Bootstrap
• Real-time Predictions: Instant results through Flask web application

🚀 Technologies Used

• Backend: Python, Flask
• Machine Learning: scikit-learn, Random Forest Classifier
• Data Processing: pandas, numpy
• Frontend: HTML, CSS, Bootstrap 5
• Model Persistence: pickle

📊 Dataset Information

The system uses comprehensive medical datasets containing:

• 41 Diseases: Including common conditions like diabetes, hypertension, allergies, etc.
• 132 Symptoms: Comprehensive symptom database for accurate predictions
• Medical Recommendations: Curated medications, diets, and workout plans for each disease

Dataset Files (located in dataset/):

• Training.csv: Main training dataset with symptoms and disease labels
• symptoms_df.csv: Symptom database with disease mappings
• description.csv: Detailed disease descriptions
• medications.csv: Medication recommendations for each disease
• diets.csv: Dietary recommendations and nutrition plans
• workout_df.csv: Exercise and workout suggestions
• precautions_df.csv: Preventive measures and precautions
• Symptom-severity.csv: Symptom severity classifications

🔧 Installation & Setup

Prerequisites

• Python 3.7+
• pip package manager

Installation Steps

1. Clone the repository:

   git clone https://github.com/sohamvsonar/Disease-Prediction-and-Medical-Recommendation-System.git
   cd Disease-Prediction-and-Medical-Recommendation-System

2. Install required dependencies:

   pip install -r requirements.txt

3. Run the Flask application:

   python main.py

4. Access the application: Open your web browser and navigate to:

   http://localhost:5000
   

📱 Usage

1. Enter Symptoms: Type your symptoms separated by commas (e.g., "fever, headache, nausea")
2. Submit: Click the predict button to get your results
3. View Results: Get comprehensive information including:
   • Predicted disease
   • Disease description
   • Recommended medications
   • Dietary suggestions
   • Exercise plans
   • Preventive precautions

👥 Team Members

• Soham Sonar
• Tanmay Pramanick
• Kunal Rajput

📸 Screenshots

🏗️ Project Structure

Disease-Prediction-and-Medical-Recommendation-System/
├── dataset/                    # Medical datasets
│   ├── Training.csv
│   ├── symptoms_df.csv
│   ├── description.csv
│   ├── medications.csv
│   ├── diets.csv
│   ├── workout_df.csv
│   ├── precautions_df.csv
│   └── Symptom-severity.csv
├── model/                      # Trained ML models
│   └── RandomForest.pkl
├── templates/                  # HTML templates
│   └── index.html
├── static/                     # Static assets
│   ├── bgCover.jpg
│   └── img.png
├── screenshots/                # Application screenshots
│   ├── ss1.jpg
│   ├── ss2.jpg
│   └── ss3.jpg
├── main.py                     # Flask web application
├── disease_prediction_system.ipynb  # Model training notebook
├── requirements.txt            # Python dependencies
└── README.md

⚠️ Disclaimer

This system is for educational and informational purposes only. It should not be used as a substitute for professional medical advice, diagnosis, or treatment. Always consult with qualified healthcare professionals for medical concerns.

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