Update README.md with detailed project description, features, quick start guide, and application sections

README.md

@@ -11,3 +11,353 @@ short_description: This tool provides early prediction and analysis for various
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 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+
+---
+
+<!-- # 🩺 AI-Powered Health & Lifestyle Disease Prediction
+
+Welcome to the **AI-Powered Health Prediction System**! 🚀
+
+This tool provides **early prediction and analysis** for various health conditions using **Machine Learning & NLP**. It is designed to assist users in understanding potential health risks based on their lifestyle and symptoms.
+
+---
+
+## 🏥 Available Features:
+
+✅ **Lifestyle Disease Predictor** (Checkbox-based system using BiomedNLP-PubMedBERT)
+
+🤖 **AI Chatbot for Health Assistance** (Ask health-related questions)
+
+🧠 **Mental Health Assessment** (Analyze sentiment & well-being)
+
+🩸 **Disease Predictors:**
+   - Diabetes
+   - Asthma
+   - Stroke
+   - Cardiovascular Disease
+
+📊 **Data Visualizer** (Analyze trends in health conditions)
+
+🛠 **User-friendly Interface** (Easy navigation and interactive elements)
+
+🔔 **Personalized Health Insights** (Recommendations based on user input)
+
+👉 **Select an option from the sidebar to proceed!**
+
+---
+
+## 🚀 Quick Start Guide
+
+1. Clone this repository:
+   ```bash
+   git clone https://github.com/MOHITRAJDEO12345/early-prediction-for-ml_proj.git
+   ```
+2. Navigate to the project directory:
+   ```bash
+   cd early-prediction-for-ml_proj
+   ```
+3. Install dependencies:
+   ```bash
+   pip install -r requirements.txt
+   ```
+4. Run the application:
+   ```bash
+   streamlit run app.py
+   ```
+
+---
+
+## 🖥 Application Sections
+
+The application includes the following navigation options:
+
+```python
+options = [
+    'Home',
+    'Checkbox-to-disease-predictor',
+    'AI Health Consultant',
+    'Mental-Analysis',
+    'Diabetes Prediction',
+    'Asthma Prediction',
+    'Cardiovascular Disease Prediction',
+    'Stroke Prediction',
+    'Sleep Health Analysis',
+    'Data Visualization',
+    'Text-based Disease Prediction'
+]
+```
+
+### 🧠 Mental Health Analysis
+- NOTE: the trained model was not upto mark so we switched to gated transformer model
+- Uses **mental/mental-roberta-base** for sentiment-based mental health assessment.
+- Predicts **Depression and Anxiety** based on user input.
+- Provides graphical risk assessment using **Seaborn & Matplotlib**.
+
+### 🔬 Disease Prediction Models
+- NOTE: only those diseases have been taken that can be predicted wihtout diagnostic results and some of the features have been discared for training
+- **Diabetes Model**: Predicts diabetes risk using medical indicators.
+- **Asthma Model**: Uses preprocessed datasets to detect asthma likelihood.
+- **Cardiovascular Model**: XGBoost-based prediction for heart disease.
+- **Stroke Model**: Uses ML models to assess stroke risk factors.
+
+### 📝 Text-based Disease Prediction
+- Uses **distilbert-base-uncased** for text-based disease prediction.
+- Allows users to input symptoms via text or audio.
+- Predicts possible lifestyle diseases based on user input.
+- Provides graphical risk assessment using **Seaborn & Matplotlib**.
+
+---
+
+## 📸 Screenshots & UI Preview
+
+🔍 **Streamlit Application Interface:**
+
+- NOTE: for functionality purpose only
+- YOUTUBE: https://youtu.be/abrRqceVuDU
+![Streamlit UI](screenshots/streamlit.png)
+
+📊 **Data Visualization Example:**
+- NOTE: currently showing datasets 
+it will be used for visualizing anomalies in user predictions it will become personalized
+![Data Visualization](screenshots/data_visual.png)
+![User Graph](screenshots/user_graph.png)
+
+🖥 **Separate Frontend Interface:**
+- NOTE: the frontend is currently not connected with ml models and it may behave wrongly
+- WORKING: https://v0.dev/chat/community/lifestyle-disease-prediction-ADp1mOc0hKg
+- YOUTUBE: https://youtu.be/DU4FW-8hSoU
+![Frontend UI](screenshots/frontend.png)
+
+---
+
+## ⚠️ Disclaimer
+
+This application has been developed using real-world healthcare datasets sourced from Kaggle:
+
+- **Stroke Prediction Dataset**
+- **Asthma Analysis & Prediction Dataset**
+- **Diabetes Dataset**
+- **Cardiovascular Disease Dataset**
+- **Sentiment Analysis for Mental Health**
+
+The predictions are generated using machine learning models trained on these datasets, incorporating evaluation metrics and graphical insights to enhance interpretability.
+
+However, this tool has **not undergone clinical validation** and should be used for **informational and educational purposes only**. It is not intended to serve as a substitute for **professional medical diagnosis or treatment**. Always consult a qualified healthcare provider for medical advice.
+
+---
+
+# colab
+- https://colab.research.google.com/drive/1DpOH7KgTWubr5qQjj13EDqxIqsbPLDQe?usp=sharing#scrollTo=EgbDF0U5L1l2
+- https://colab.research.google.com/drive/1GI7Z1GPPUi67X6UssCQVJXr_QoysfJrz#scrollTo=XkcDpRRzFCIX
+- https://colab.research.google.com/drive/1eZIBboyY_x0ZsJp5G10XrFFu4aG4eCuf#scrollTo=3NDJOlrEpmoL
+- http://colab.research.google.com/drive/11KO6cvyTeYY_v5PnYqTwheEupJtNjfCr?usp=sharing#scrollTo=7EyXbXJkPnqf
+- https://colab.research.google.com/drive/1-B7Q8hXHD0iIBvVldnLkvCiWGhJ2iYNL?usp=sharing
+- https://colab.research.google.com/drive/1inXO2_JvTw6fOXiJGaW_0pJvI_3sNo0T?usp=sharing
+- https://colab.research.google.com/drive/1NpwO0NBOKQBtUuN9cC-CXE4vuP5TCavY?usp=sharing
+- https://colab.research.google.com/drive/10W68SdZHS3IvJAjFTBoqEFI5g7USZVo9?usp=sharing
+- https://colab.research.google.com/drive/1J8xvEs7rDn0NLYIzH5S2UgFt-lOk7TA6?usp=sharing
+- https://colab.research.google.com/drive/1BeDmCVjVLb3uqUHdnafgLMLItAtgsAsN?usp=sharing
+- 
+---
+
+## 📌 Modular Features (Pending Integration)
+
+Several functionalities have been implemented but are pending Streamlit integration for optimization:
+
+✅ **User Login & Basic Inputs**: Secure authentication and user profile management.
+✅ **Personalized Email Reports**: Automated daily, weekly, and monthly health insights.
+✅ **Anomaly Visualization**: Analyzes past predictions to detect anomalies.
+✅ **Workout Plans**: AI-driven personalized workout routines based on health data.
+✅ **Sleep Analysis**: AI-powered sleep tracking and recommendations.
+✅ **Medication Adherence**: Reminders and tracking for prescribed medications.
+✅ **Nutrition Recommendations**: AI-based meal planning and dietary suggestions.
+✅ **Community & Resources**: A section for health articles, discussions, and expert Q&A.
+
+---
+
+## 🔬 Ongoing Research & Future Enhancements
+
+🚧 **Fitbit API Integration** – Real-time health monitoring with wearable devices.
+🚧 **LSTM Models for Realtime Fitbit Data** – Developing deep learning models for dynamic health tracking.
+🚧 **Enhanced Mental Health Analysis** – Exploring transformer-based sentiment models for deeper insights.
+🚧 **Hybrid ML & NLP Systems** – Combining structured health data with unstructured text for more accurate predictions.
+
+---
+
+## 👨‍💻 Author
+
+Developed by **Mohit Rajdeo**  
+GitHub: [MOHITRAJDEO12345](https://github.com/MOHITRAJDEO12345)
+
+---
+
+## 🤝 Contributions
+
+Contributions are always welcome! Feel free to open an issue or submit a pull request if you have suggestions or improvements.
+
+---
+
+## 📬 Contact
+
+For any questions or feedback, feel free to reach out:
+
+📧 Email: [email protected]  
+🐦 Twitter: [@mohitrajdeo](https://twitter.com/mohitrajdeo) -->
+
+
+
+# 🩺 Early Prediction of Health & Lifestyle Diseases
+
+Welcome to the **AI-Powered Health Prediction System**! 🚀
+
+This tool provides **early prediction and analysis** for various health conditions using **Machine Learning & NLP**. It assists users in understanding potential health risks based on their lifestyle, medical indicators, and symptoms.
+
+---
+
+## 🏥 Available Features:
+
+✅ **Diabetes Prediction** – Predict diabetes risk using medical indicators.
+
+✅ **Hypertension Prediction** – Assess the risk of high blood pressure.
+
+✅ **Cardiovascular Disease Prediction** – XGBoost-based prediction for heart disease.
+
+✅ **Stroke Prediction** – Machine Learning-based stroke risk analysis.
+
+✅ **Asthma Prediction** – Detect asthma likelihood using preprocessed datasets.
+
+✅ **Sleep Health Analysis** – AI-driven analysis of sleep patterns and health.
+
+✅ **Mental Health Assessment** – Sentiment-based analysis using **mental-roberta-base**.
+
+✅ **Medical Consultant AI Chatbot** – Ask health-related questions for AI-driven insights.
+
+✅ **Data Visualization** – Graphical representation of health trends and anomalies.
+
+👉 **Select an option from the sidebar to proceed!**
+
+---
+
+## 🚀 Quick Start Guide
+
+1. Clone this repository:
+   ```bash
+   git clone https://github.com/MOHITRAJDEO12345/early-prediction-for-ml_proj.git
+   ```
+2. Navigate to the project directory:
+   ```bash
+   cd early-prediction-for-ml_proj
+   ```
+3. Install dependencies:
+   ```bash
+   pip install -r requirements.txt
+   ```
+4. Run the application:
+   ```bash
+   streamlit run app.py
+   ```
+
+---
+
+## 🖥 Application Sections
+
+The application includes the following navigation options:
+
+```python
+options = [
+    'Home',
+    'Diabetes Prediction',
+    'Hypertension Prediction',
+    'Cardiovascular Disease Prediction',
+    'Stroke Prediction',
+    'Asthma Prediction',
+    'Sleep Health Analysis',
+    'Mental-Analysis',
+    'Medical Consultant',
+    'Data Visualization'
+]
+```
+
+### 🧠 Mental Health Analysis
+- Uses **mental/mental-roberta-base** for sentiment-based mental health assessment.
+- Predicts **Depression and Anxiety** based on user input.
+- Provides graphical risk assessment using **Seaborn & Matplotlib**.
+
+### 🔬 Disease Prediction Models
+- **Diabetes Model**: Predicts diabetes risk based on medical data.
+- **Hypertension Model**: Evaluates high blood pressure risk.
+- **Cardiovascular Model**: Uses XGBoost for heart disease prediction.
+- **Stroke Model**: ML-based assessment of stroke risk factors.
+- **Asthma Model**: Machine learning model for asthma detection.
+
+### 📊 Data Visualization
+- Interactive graphs to analyze health trends.
+- Anomaly detection for user predictions.
+
+### 🤖 AI Medical Consultant
+- AI-powered chatbot for answering health-related queries.
+- Uses NLP models for better understanding and recommendations.
+
+---
+
+## 📸 Screenshots & UI Preview
+
+🔍 **Streamlit Application Interface:**
+![Streamlit UI](screenshots/streamlit.png)
+
+📊 **Data Visualization Example:**
+![Data Visualization](screenshots/data_visual.png)
+![User Graph](screenshots/user_graph.png)
+
+🖥 **Separate Frontend Interface:**
+![Frontend UI](screenshots/frontend.png)
+
+---
+
+## ⚠️ Disclaimer
+
+This application has been developed using real-world healthcare datasets sourced from Kaggle:
+
+- **Diabetes Dataset**
+- **Hypertension Dataset**
+- **Cardiovascular Disease Dataset**
+- **Stroke Prediction Dataset**
+- **Asthma Analysis & Prediction Dataset**
+- **Sentiment Analysis for Mental Health**
+
+The predictions are generated using machine learning models trained on these datasets, incorporating evaluation metrics and graphical insights to enhance interpretability.
+
+However, this tool has **not undergone clinical validation** and should be used for **informational and educational purposes only**. It is not intended to serve as a substitute for **professional medical diagnosis or treatment**. Always consult a qualified healthcare provider for medical advice.
+
+---
+
+# 🔬 Ongoing Research & Future Enhancements
+
+🚧 **Fitbit API Integration** – Real-time health monitoring with wearable devices.
+🚧 **LSTM Models for Realtime Fitbit Data** – Developing deep learning models for dynamic health tracking.
+🚧 **Enhanced Mental Health Analysis** – Exploring transformer-based sentiment models for deeper insights.
+🚧 **Hybrid ML & NLP Systems** – Combining structured health data with unstructured text for more accurate predictions.
+
+---
+
+## 👨‍💻 Author
+
+Developed by **Mohit Rajdeo**  
+GitHub: [MOHITRAJDEO12345](https://github.com/MOHITRAJDEO12345)
+
+---
+
+## 🤝 Contributions
+
+Contributions are always welcome! Feel free to open an issue or submit a pull request if you have suggestions or improvements.
+
+---
+
+## 📬 Contact
+
+For any questions or feedback, feel free to reach out:
+
+📧 Email: [email protected]  
+🐦 Twitter: [@mohitrajdeo](https://twitter.com/mohitrajdeo)
+