metadata

title: Early-prediction-for-ml Proj
emoji: 📉
colorFrom: blue
colorTo: green
sdk: streamlit
sdk_version: 1.44.0
app_file: app.py
pinned: false
short_description: This tool provides early prediction and analysis for various

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

🩺 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

Clone this repository:

git clone https://github.com/MOHITRAJDEO12345/early-prediction-for-ml_proj.git

Navigate to the project directory:
```
cd early-prediction-for-ml_proj
```
Install dependencies:
```
pip install -r requirements.txt
```
Run the application:
```
streamlit run app.py
```

🖥 Application Sections

The application includes the following navigation options:

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:

📊 Data Visualization Example:

🖥 Separate Frontend Interface:

⚠️ 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

🤝 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