A CONTEXT-AWARE MOBILE APP TO SUPPORT EARLY DISEASE DETECTION AND EDUCATION USING GPT-4 AND VISUAL SYMPTOM SURVEYS

This research project addresses the growing gap in accessible healthcare, particularly for women in underserved communities [1]. Rising healthcare costs and delayed diagnosis contribute to higher mortality, particularly in low-income areas. To address this, we developed CareBridge Health, a mobile app that uses AI (GPT-4) to simulate medical reasoning based on structured user input [2]. The app features a body diagram for symptom selection, guided surveys for pain description, and access to disease education through multimedia content. The system is divided into three components: the Ask Page for diagnosis, the Learn Page for information retrieval, and the History Page for recordkeeping. Through two experiments, we identified that both symptom clarity and AI consistency can affect diagnosis quality [3]. Despite these limitations, the app provides a scalable, low-cost way to raise health awareness and guide users toward early symptom identification. With further refinement and medical validation, CareBridge Health could become a valuable tool for community-level health empowerment.