The Symptom Solver is an AI-powered platform that predicts diseases based on user-reported symptoms using advanced Natural Language Processing (NLP) and Machine Learning techniques.
It provides an intuitive interface to deliver:
- Accurate disease predictions
- Preventive measures
- Natural treatment suggestions
This project enhances healthcare accessibility by allowing users to input symptoms in plain language and receive instant diagnosis and advice. It is designed to help users get quick health insights from anywhere — no clinical visit required.
- 🩺 NLP-based symptom understanding
- 📋 Disease prediction using trained models
- 💡 Preventive and natural remedies
- 🌐 User-friendly web interface
- ⚡ Instant AI-powered health feedback
- Python 3
- Natural Language Toolkit (NLTK) / spaCy
- scikit-learn / Transformers
- Pandas, NumPy
- Flask (for backend API)
- HTML, CSS (frontend)
- Users enter symptoms in natural language (e.g., "I have fever and headache").
- NLP processes and extracts key symptoms.
- ML model matches symptoms to probable diseases.
- The system returns:
- Disease prediction
- Precautions
- Natural treatment options
Symptom_Solver---Disease_diagnosis_using_NLP/ │ ├── data/ # Datasets for training/testing ├── models/ # Trained ML/NLP models ├── templates/ # HTML templates ├── static/ # CSS and JS files ├── app.py # Main application file (Flask) ├── requirements.txt # Python dependencies └── README.md # Project overview
git clone https://github.com/gopireddy99/Symptom_Solver---Disease_diagnosis_using_NLP.git cd Symptom_Solver---Disease_diagnosis_using_NLP pip install -r requirements.txt python app.py
🌍 Multilingual symptom input support
🤖 Integration with wearable health devices
💬 Interactive AI chatbot for Q&A
📱 Mobile-friendly UI
👨💻 Nithish Kumar Gopireddy 📧 Email: gopireddynithishkumar@gmail.com 🔗 GitHub: gopireddy99
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