Mediconnect

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Inspiration

I was inspired to create Mediconnect because of my family. My parents are both doctors, and my brother is a medical student. Growing up, I always heard them talk about their work—both the amazing things they could do for patients and the challenges they faced.

I saw a need for a single platform that could help everyone in healthcare. I wanted to build a website that could:

Help patients get help fast, especially in an emergency.

Give doctors and residents AI-powered tools to help them make diagnoses.

Give students a better way to study and learn.

Mediconnect is my way of using technology to try and solve some of the problems I've seen them face.

What it does

Mediconnect is an all-in-one website that connects patients, doctors, and students.

For Patients:

AI Symptom Checker: You can describe your symptoms to an AI (Google Gemini), which suggests what might be wrong and what kind of doctor you should see.

Real Doctor Matching: The site then searches a massive, real-world database (a 704MB file) of actual doctors to find one who matches that specialty.

Easy Booking: You can see the doctor's location on a map and book an appointment right from the site.

Emergency SOS: If you're a registered user, you can use an emergency button to send your exact location to get help.

For Doctors & Residents:

AI Support: Professionals can use the AI to get a "second opinion" or ideas for different diagnoses and treatment plans.

For Medical Students:

Learning Hub: We built a section called the "Clinical Nexus Academy" with quizzes, case studies, and game-like elements to make learning more interactive.

How we built it

We built Mediconnect as a full-stack web application.

Frontend (What you see): We used React and Vite to build a fast, modern user interface. This includes all the pop-up windows (like BookingModal.jsx) and the map.

Backend (What runs on the server): We used Node.js and Express to build the "brain" of the website. This handles all the user requests and data.

Data & AI:

We used the Google Gemini AI to power the symptom checker and all the learning tools.

The core of our doctor search is a real 704MB government file of doctors and clinicians. We wrote a custom script (csvProcessor.js) to read and search this huge file instantly.

We used SQLite for our database to keep track of things like user appointments.

Challenges we ran into

Handling the 704MB File: This file was huge. Our biggest challenge was figuring out how to make our server search it quickly without crashing or timing out. We had to write a very specific script to handle this.

The "Missing Address" Bug: We had a bug where the doctor's address wouldn't show up in the booking modal or on the map. Our code logs just said address: undefined. This was a tricky problem with how we were passing data between different parts of our React app.

Random Errors: We also spent a lot of time hunting down a vague Uncaught SyntaxError that was hard to find and fix.

Accomplishments that we're proud of

Making the Doctor Search Work: We are most proud of getting the search to work with that giant 704MB file. It means our app provides users with real doctors, not just fake data.

Using AI in Three Ways: We didn't just add a chatbot. We successfully used AI to help patients, educate students, and support doctors, all in different ways.

A Complete, Working App: We built a full, end-to-end experience. A user can start by describing their symptoms and end by booking an appointment with a real doctor, all in one place.

What we learned

"Big Data" is Harder Than it Looks: Working with a 704MB file taught us that real-world data is messy and difficult. We had to learn advanced Node.js techniques to process it correctly.

Managing App Data is Key: The "missing address" bug was a powerful lesson. It taught us how important it is to be careful and organized when passing data around in a React application.

Using Real Data is Motivating: Using a real government list of doctors made the project feel much more important and pushed our team to build a high-quality product.

What's next for Mediconnect

Now that we've fixed the booking modal bug and upgraded the emergency location tracking, we can focus on expanding the platform's features:

Integrate a Payment System: We plan to build in a secure payment portal so patients can pay for their appointments directly through the app.

Expand the Student Academy: We will build out the "interactive game-like elements" for the Clinical Nexus Academy to create a more engaging learning simulation for students.

Keep the Data Fresh: We want to write a script that automatically downloads and processes the latest version of the CMS clinician database to keep our doctor list accurate and up-to-date.

Built With

• api
• gemini
• git
• github
• libraries
• react
• restful-web-services-bible
• vite