Mental-depression-Measures

Aspirise - A Complete Wellness Advisor

Aspirise is an AI-powered wellness advisor designed to detect and support mental health needs on an individual basis. Our goal is to provide comprehensive mental health solutions tailored to each user's unique circumstances, empowering them to achieve holistic well-being.

Table of Contents

• Project Overview
• Key Features
• Phase Details
  • Phase 1
  • Phase 2
  • Phase 3
• Installation
• Usage
• Contributing
• License
• Acknowledgements
• Contact

Project Overview

Aspirise aims to be a comprehensive, empathetic wellness advisor that addresses the mental health needs of individuals through personalized, AI-driven solutions. By offering tailored support and resources, Aspirise empowers users to manage their mental health proactively, leading to improved overall well-being and resilience.

Key Features

• AI-Driven Mental Health Detection
• Personalized Wellness Plans
• Educational Resources
• Real-Time Support
• Progress Tracking and Monitoring
• Community Engagement
• Crisis Intervention

Phase Details

Phase 1: AI-Driven Mental Health Detection and Educational Resources

Description: In this initial phase, Aspirise focuses on the core functionality of detecting mental health conditions using AI. Users can take assessments that analyze their mental health status through self-reported data and behavioral patterns. This phase also offers a comprehensive library of educational resources on various mental health topics.

Key Components:

• Dataset Preparation: Collecting and preprocessing data.
• Model Training: Using Python, scikit-learn, and logistic regression.
• Evaluation: Ensuring model accuracy, precision, and recall.

Phase 2: Personalized Wellness Plans and Real-Time Support

Description: Building on the foundational AI detection capabilities, Phase 2 introduces personalized wellness plans tailored to each user's unique needs. This phase also offers real-time support through chatbots and connections to professional help.

Key Components:

• Personalization Algorithms: Enhancing recommendations.
• User Interface: Developing intuitive interfaces for interaction.
• Professional Integration: Connecting users to professional support.

Phase 3: Progress Tracking, Community Engagement, and Crisis Intervention

Description: The final phase focuses on long-term engagement and support. Users have tools to track their mental health progress over time, engage with a supportive community, and access crisis intervention resources when needed.

Key Components:

• Progress Monitoring: Tools for tracking mental health.
• Community Features: Forums and virtual meet-ups.
• Crisis Support: Emergency contacts and immediate assistance.

Installation

To install and run Aspirise locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/shamblessss/Mental-depression-Measures.git

2. Navigate to the project directory:

   cd aspirise

Usage

1. Prepare the dataset by placing it in the data/ directory.
2. Run the preprocessing script:

   python preprocess.py

3. Train the model:

   python train_model.py

4. Start the application:

   python app.py

Contributing

We welcome contributions to Aspirise! To contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature/your-feature-name

3. Make your changes.
4. Commit your changes:

   git commit -m 'Add some feature'

5. Push to the branch:

   git push origin feature/your-feature-name

6. Open a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgements

We would like to thank our project team members and contributors for their dedication and hard work. Special thanks to our advisors and mental health experts for their invaluable insights.

Contact

For any questions or suggestions, please reach out to us at:

• Email: sanjanacharaya1234@gmail.com
• LinkedIn: Author LinkedIn

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