My team reached the final round with a system for screening urinary stone risk, designed for local health centers. It combines hardware, a web app, and AI to screen patients and store data in a central database.
My team was selected as one of the top 10 finalists out of 308 teams in the “Samsung Solve for Tomorrow” program. I developed a system to assess urinary stone risk using object detection on urine components, aiming to reduce the diagnostic workload for healthcare professionals.
My team won the Hackathon round and placed 3rd in the Sandbox round of the “PTT Group Young Socialpreneur Hackathon,” competing with startups and private companies. Our AI-based project focused on community medicine, making patient screening more accessible and affordable to underserved areas.