symptector

Landing page of the health ai
Chatting and predication part of the ai
Showing the predication money
Ask extra symptom for predication
Solution and Final disease Answer

Inspiration

In many parts of the world, people suffer from diseases — and sadly, some lose their lives simply because they don’t know how to protect themselves in time. For many, it’s not just lack of awareness, but also lack of access. Some can’t afford medicine. Others don’t get help soon enough.

💡 "This is what inspired me to build this system — a prototype Health AI Assistant where anyone can enter their symptoms and receive reliable guidance, including simple home remedies."

🌟 "My goal is to develop this further and provide a service that’s accessible to everyone — because I believe health support should not depend on wealth or location."

What it does

This is a simple yet powerful system where users can enter their symptoms. The AI analyzes those symptoms using machine learning — trained on a reliable dataset — and provides trustworthy solutions and guidance

How we built it

This system is built with the support of Bolt.New for the UI design, while all the core logic is handled entirely by us. We’ve used technologies like HTML, CSS, JavaScript, and Brain.js to create the machine learning model. The best part? We didn’t rely on any external APIs or third-party services — everything, including the dataset collection and AI logic, is built from scratch by me and some Ai tool.

Challenges we ran into

While building this system, I faced some challenges. One was creating a reliable dataset and designing solutions that could truly help users. Another challenge was developing the logic — especially making sure the system could ask for extra symptoms when needed, to provide a better and more accurate analysis. That part took me a bit more time to get right. In the deployment phase, I initially tried to deploy using Bolt.New. However, I ran into an issue where only one page would upload — the other page didn’t connect properly, likely due to a communication problem between Bolt and Netlify. To solve this, I exported the project and deployed it manually, ensuring everything worked as intended.

Accomplishments that we're proud of

We are proud to have built a system that can support individual lives by addressing one of the most important needs of every person — their health. This is more than just technology; it’s about making a meaningful difference. And if we dare to think big, we can make the impossible possible — because when we have a clear vision, the road begins to create itself.

What we learned

Through this project, I’ve learned so much — especially about machine learning: how it works, how to train it, and how to apply it in real life. We’ve built a system with real potential to help people, and what’s exciting is that we didn’t need a massive computer setup or a large team of developers. What matters is the willingness to try. Because even if we don’t succeed at first, we gain valuable knowledge — and that is success in itself.

What's next for symptector

In the future, my goal is to collect more comprehensive datasets and collaborate with doctors to create even more reliable solutions for everyone. I want to make this service available to as many people as possible and continuously upgrade the dataset so that it can address a wider range of health conditions. By doing this, we can improve the accuracy, reliability, and professionalism of the system — and truly make a difference in healthcare.