Skip to main content

Mental Health Prediction Using Machine Learning: Building an Explainable AI Web Application

Machine learning is increasingly being explored for applications in healthcare and wellbeing. However, building an ML model for a sensitive domain such as mental health requires more than simply achieving a high accuracy score. I developed a Mental Health Prediction & Assessment System that combines machine learning, PHQ-9 screening, Explainable AI and a Flask-based web application. The project is available on GitHub: https://github.com/starJeet000/Mental-Health-Prediction-Using-Machine-Learning What Is the Project? The application is designed as an educational and preliminary screening system that evaluates mental-health-related information and produces a risk prediction. It combines an ML-based prediction system with a standardized PHQ-9 questionnaire. The purpose is not to replace mental-health professionals but to demonstrate how machine learning can be incorporated into a complete software application. Machine Learning Model Several classification algorithms were tr...

Privacy Policy

Welcome to The Lazy Dev Hub.

Last updated: August 12, 2026

Your privacy is important to us. This Privacy Policy explains how information may be collected, used, and protected when you visit our website.

Website: https://thelazydevhub.blogspot.com/

1. Information We Collect

The Lazy Dev Hub does not intentionally collect personally identifiable information from visitors unless visitors voluntarily provide it.

For example, if you contact us by email, we may receive information such as your email address, name, and the information included in your message.

2. Automatically Collected Information

Like many websites, Blogger and third-party services used by this website may automatically collect certain technical information about visitors.

This may include information such as:

  • IP address

  • Browser type

  • Device type

  • Operating system

  • Referring pages

  • Pages visited

  • Approximate usage information

  • Date and time of visits

This information may be used for security, analytics, website improvement, and understanding how visitors use the website.

3. Cookies

The website and third-party services may use cookies or similar technologies.

Cookies are small files stored on your device that can help websites remember information and understand how visitors interact with websites.

You can configure your browser to refuse or delete cookies. However, some website functionality may be affected.

4. Google AdSense and Advertising

The Lazy Dev Hub may use Google AdSense or other third-party advertising services to display advertisements.

Third-party advertising providers may use cookies and similar technologies to provide advertisements and measure advertising performance.

Google may use advertising cookies to help serve ads based on a user's visits to this and other websites.

You can learn more about Google's advertising practices and privacy options through Google's official resources.

5. Analytics

We may use analytics or similar services to understand website traffic and improve the content and user experience.

These services may collect information about how visitors interact with the website.

6. Third-Party Links

Our articles may contain links to third-party websites, tools, products, services, or resources.

We are not responsible for the privacy practices, security, content, or policies of third-party websites.

Visitors should review the privacy policies of external websites before providing personal information.

7. Children's Privacy

The Lazy Dev Hub does not knowingly collect personal information from children for the purpose of creating personal profiles or accounts.

Parents or guardians who believe that a child has provided personal information to us may contact us so that the situation can be reviewed.

8. Data Security

We take reasonable steps to protect information under our control. However, no method of transmission or storage over the internet can be guaranteed to be completely secure.

9. Changes to This Privacy Policy

This Privacy Policy may be updated from time to time to reflect changes in our website, services, technology, or applicable requirements.

Any changes will be posted on this page with an updated date.

10. Contact

If you have questions about this Privacy Policy, please contact us through our Contact page.

The Lazy Dev Hub

Website: https://thelazydevhub.blogspot.com/

Comments

Popular posts from this blog

The Complete AI + Cybersecurity + MERN Developer Roadmap for 2026

Artificial intelligence, cybersecurity, and web development are three of the most interesting areas of modern technology. Each field provides valuable career opportunities on its own. But combining them can create an especially powerful technical skill set. This roadmap is designed for developers and students who want to learn MERN + cybersecurity + AI and eventually build real-world applications that combine all three. Why Learn AI + Cybersecurity + MERN? Consider a modern security application. A user opens a React dashboard. The application sends information to a Node.js backend. The backend stores data in MongoDB. Security rules analyze the data. An AI service helps classify or summarize the results. That single system requires knowledge of: Frontend development Backend development Databases APIs Security AI Deployment This is the intersection we are targeting. Phase 1: Learn Web Fundamentals Start with: HTML CSS JavaScript HTTP REST APIs Git GitHub Do not rush into advanced AI bef...

Mental Health Prediction Using Machine Learning: Building an Explainable AI Web Application

Machine learning is increasingly being explored for applications in healthcare and wellbeing. However, building an ML model for a sensitive domain such as mental health requires more than simply achieving a high accuracy score. I developed a Mental Health Prediction & Assessment System that combines machine learning, PHQ-9 screening, Explainable AI and a Flask-based web application. The project is available on GitHub: https://github.com/starJeet000/Mental-Health-Prediction-Using-Machine-Learning What Is the Project? The application is designed as an educational and preliminary screening system that evaluates mental-health-related information and produces a risk prediction. It combines an ML-based prediction system with a standardized PHQ-9 questionnaire. The purpose is not to replace mental-health professionals but to demonstrate how machine learning can be incorporated into a complete software application. Machine Learning Model Several classification algorithms were tr...

Gemini API + Node.js: Building Your First AI-Powered App

Artificial intelligence APIs make it possible for web developers to add AI capabilities without training a machine-learning model from scratch. A Node.js backend can communicate with an AI service, process the response, and provide the result to a React frontend. This architecture can be used for chatbots, document analysis, cybersecurity applications, content tools, and many other projects. Basic Architecture A simple AI-powered application can look like: React Frontend ↓ Node.js / Express ↓ AI API ↓ Node.js ↓ React The most important design principle is that private API credentials should remain on the server. 1. Create the Node.js Application Start with a Node.js backend and an Express API. The backend should contain separate responsibilities for: Routes Controllers AI service logic Validation Error handling Keeping these responsibilities separated makes the application easier to maintain. 2. Protect Environment Variables AI API credentials should not be hard...