Care lens

CareLens: AI-Powered Health Risk Assessment

Inspiration

In today's world, proactive healthcare is more important than ever. Many individuals are unaware of their potential health risks for chronic diseases like diabetes, heart disease, and stroke until it's too late. We were inspired to create CareLens to empower people with accessible, AI-driven tools to understand their health risks early and connect them with the care they need.

What it does

CareLens is an intelligent health risk assessment platform that uses machine learning to analyze user-provided health data and medical documents. It provides personalized risk scores for a variety of chronic conditions, explains the contributing factors, and helps users find nearby healthcare providers.

How we built it

CareLens is built with a modern, robust technology stack:

Frontend: Next.js, React, TypeScript, Tailwind CSS, and shadcn/ui for a responsive and intuitive user experience.
Backend: FastAPI and Python for a high-performance, scalable API.
Machine Learning: scikit-learn, XGBoost, and LightGBM to build and serve our risk assessment models.
Database & Caching: Redis for session management and caching.
Deployment: Docker and Vercel for continuous integration and deployment.

Challenges we ran into

One of the biggest challenges was ensuring the privacy and security of user data. We implemented a "privacy-by-design" architecture, with no persistent storage of personal health information and a stateless backend. Another challenge was the complexity of interpreting medical documents. We are actively working on a robust document processing pipeline using OCR and NLP to accurately extract information from lab reports.

Accomplishments that we're proud of

We are proud to have built a functional prototype with a polished user interface and a working backend that can serve machine learning models. We have also created a comprehensive set of documentation that outlines our vision, architecture, and future roadmap.

What we learned

This project has been a valuable learning experience in full-stack development, machine learning engineering, and the importance of user-centric design in healthcare technology. We've learned how to build and integrate complex systems, and the challenges of working with sensitive data.

What's next for CareLens

We have an ambitious roadmap for CareLens, including:

Expanding the number of supported health conditions.
Improving the accuracy of our document processing pipeline.
Integrating with wearable devices to capture real-time health data.
Building a mobile application for on-the-go access.
Partnering with healthcare providers to integrate CareLens into their workflows.