Inspiration
Health risks often go unnoticed until it's too late. We wanted to create a simple, accessible tool that helps users assess their lifestyle choices and become more proactive about their well-being. By providing instant feedback on potential health risks, we aim to encourage early awareness and smarter health decisions.
What it does
Medi-QR is a health risk assessment tool that calculates a personalized risk score based on user responses to lifestyle-related questions. Users answer questions about habits like smoking, exercise, and diet, and the app generates a risk score, offering insights into potential health concerns.
How we built it
We developed Medi-QR using JavaScript with the React framework for the front end, ensuring a smooth and responsive user experience. On the backend, we built a RESTful API using Node.js with JavaScript, handling data processing and risk score calculations efficiently.
Challenges we ran into
Our biggest challenge was connecting the front end to the backend, as we initially struggled to get both running properly together. We also faced difficulties in figuring out how to run our website correctly, which required troubleshooting deployment issues and carefully reviewing our GitHub commit history for insights. Additionally, we had to ensure that backend requests were managed efficiently while maintaining smooth communication with the frontend. Although we attempted to use Python with Flask to parse data, we couldn’t fully integrate it in time but plan to incorporate it in future iterations.
Accomplishments that we're proud of
We are proud of successfully setting up a full-stack application within the hackathon timeframe. One of our key accomplishments was troubleshooting deployment issues by documenting crucial details in our README file, which helped us realize that we needed to use a split terminal to run the front end and backend simultaneously. Additionally, we designed a clean and intuitive UI with React, ensuring a smooth and user-friendly experience.
What we learned
Through this project, we learned how to connect a React front end with a Node.js backend and debug API issues. We also saw how important documentation is, as checking our GitHub history and README helped us fix problems. Lastly, we learned how to improve scalability by exploring ways to make our risk assessments more accurate.
What's next for Medi-QR
We plan to integrate parsed data with an API to improve the accuracy of our health risk assessments. We also want to expand our questionnaire to include more lifestyle and medical factors for a more comprehensive evaluation. Additionally, we aim to implement QR code functionality, making it easier for users to access their assessments from healthcare providers, gyms, or wellness centers.
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