MythBuster AI Project Overview

Inspiration

The inspiration for MythBuster AI came from the increasing spread of health misinformation online. With many people relying on social media for health advice, we recognized the urgent need for a reliable tool that helps users distinguish between fact and fiction. Our goal was to create an accessible platform that empowers individuals to make informed health decisions based on accurate evaluations of common health myths.

What it does

MythBuster AI is an interactive application that evaluates health myths using the Gemini API. Users can input any health-related statement, and the app provides a clear evaluation—true or false—along with a detailed explanation. The results are presented in a visually engaging format, featuring rich text that enhances understanding and encourages users to learn more about the topic.

How we built it

We built MythBuster AI using Next.js for the frontend, which allows for a responsive and user-friendly experience. The application leverages the Gemini API to process user inputs and generate evaluations. Our backend API facilitates communication between the frontend and the Gemini API, ensuring smooth data flow. We also implemented DOMPurify to safely render rich text in the evaluation results, enhancing user experience while maintaining security.

Challenges we ran into

One of the main challenges we faced was ensuring the accuracy and reliability of the AI-generated evaluations. It was crucial to balance the complexity of health information with user-friendly explanations. Additionally, we encountered technical hurdles related to API integration and sanitizing HTML content to prevent security vulnerabilities. Overcoming these challenges required extensive testing and collaboration among team members.

Accomplishments that we're proud of

We are proud to have developed an intuitive application that effectively addresses a critical need for reliable health information. Successfully integrating the Gemini API for myth evaluation and implementing robust security measures to protect users are significant achievements. Furthermore, receiving positive feedback from early users affirmed the app's value and potential impact in combating health misinformation.

What we learned

Throughout the development of MythBuster AI, we learned the importance of thorough research and validation when dealing with health information. We gained valuable insights into the complexities of API integration and the necessity of user experience design. Collaborating as a team allowed us to leverage diverse skills and perspectives, leading to creative solutions for the challenges we encountered.

What's next for MythBuster AI

Looking ahead, we plan to enhance MythBuster AI by expanding its knowledge base to cover a wider range of health topics and myths. We aim to incorporate user feedback mechanisms to continually improve the app's functionality and accuracy. Additionally, we envision developing mobile app versions to reach a broader audience, making reliable health information accessible to everyone, anytime, anywhere.

Built With

• gemini
• nextjs