Update README.md

README.md

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-# AI Medical Consultation System
-
-An intelligent medical consultation system built with Streamlit that uses multiple AI models to analyze patient symptoms, assess risk levels, and provide personalized medical recommendations.
-
-## 🚀 Features
-
-- **Natural Language Symptom Description**: Patients describe their symptoms in natural language
-- **Symptom Extraction**: Automatically extracts key symptoms and duration information using BioBERT
-- **Risk Assessment**: Classifies the risk level (Low, Medium, High) using PubMedBERT
-- **Personalized Recommendations**: Generates tailored medical recommendations using a fine-tuned T5 model
-- **User-Friendly Interface**: Clean, intuitive UI with interactive visualizations
-- **Consultation History**: Save and review past consultations
-- **Responsive Design**: Works on desktop and mobile devices
-
-## 📋 System Components
-
-The system consists of three AI models working in a pipeline:
-
-1. **Symptom Extraction Model**: [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1)
-   - Identifies symptoms and their duration in the patient's description
-   - Implemented as a Named Entity Recognition (NER) task
-
-2. **Risk Classification Model**: [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract)
-   - Classifies the patient's condition into Low, Medium, or High risk
-   - Fine-tuned for medical risk assessment
-
-3. **Recommendation Generation Model**: Fine-tuned T5-small
-   - Generates personalized medical recommendations
-   - Fine-tuned on a dataset of medical advice and recommendations
-
-## 🛠️ Installation
-
-1. Clone this repository:
-```bash
-git clone <repository-url>
-cd medical-consultation-system
-```
-
-2. Install the required packages:
-```bash
-pip install -r requirements.txt
-```
-
-3. Download the fine-tuned T5 model (if not included):
-```bash
-# Instructions for downloading or fine-tuning the T5 model would go here
-# For example:
-# python download_models.py
-```
-
-## 🚀 Usage
-
-1. Run the Streamlit app:
-```bash
-streamlit run app.py
-```
-
-2. Open your web browser and navigate to the URL displayed in your terminal (typically http://localhost:8501)
-
-3. Enter your symptoms in natural language in the text area
-
-4. Click the "Analyze Symptoms" button to process your input
-
-5. Review the results in the various tabs:
-   - **Overview**: Summary of symptoms, risk level, and recommendations
-   - **Symptoms Analysis**: Detailed analysis of extracted symptoms and duration
-   - **Risk Assessment**: Risk level with confidence and explanation
-   - **Recommendations**: Detailed medical recommendations and department suggestions
-
-## 📊 Example
-
-Input:
-```
-I've been experiencing severe headaches and dizziness for about 2 weeks. Sometimes I also feel nauseous.
-```
-
-Output:
-- **Extracted Symptoms**: Headaches, dizziness, nauseous
-- **Duration**: 2 weeks
-- **Risk Level**: Medium
-- **Recommendation**: Personalized guidance on seeking medical attention and home care
-
-## 📁 Project Structure
-
-```
-medical-consultation-system/
-├── app.py                  # Main Streamlit application
-├── models.py               # Model loading and inference code
-├── utils.py                # Helper functions and utilities
-├── style.css               # Custom CSS styling
-├── requirements.txt        # Package dependencies
-├── README.md               # Project documentation
-└── consultation_history/   # Stored consultation records (created on first use)
-```
-
-## ⚠️ Limitations and Disclaimer
-
-- This system is for **informational purposes only** and is not a substitute for professional medical advice, diagnosis, or treatment.
-- The AI models may not capture all symptoms or correctly assess all conditions.
-- Risk assessments and recommendations are based on general patterns and may not be accurate for specific individual cases.
-- Always consult with qualified healthcare providers for medical concerns.
-
-## 🔧 Customization
-
-You can customize the system by:
-- Fine-tuning the models on different or additional datasets
-- Modifying the UI in app.py
-- Adjusting the CSS styling in style.css
-- Adding new features like multilingual support or additional visualization options
-
-## 📝 License
-
-This project is licensed under the MIT License - see the LICENSE file for details.
-
-## 🙏 Acknowledgements
-
-- [Hugging Face](https://huggingface.co/) for providing access to pre-trained models
-- [Streamlit](https://streamlit.io/) for the web application framework
-- [Plotly](https://plotly.com/) for interactive visualizations 
+---
+title: FinalProject
+emoji: 🚀
+colorFrom: red
+colorTo: red
+sdk: docker
+app_port: 8501
+tags:
+- streamlit
+pinned: false
+short_description: deep learning final project
+---
+
+# Welcome to Streamlit!
+
+Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+
+If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
+forums](https://discuss.streamlit.io).