Xintong Wu¹ and Tiancheng Xu², ¹Shenzhen College of International Education, Guangdong, ²California State Polytechnic University, USA

This paper presents the design, implementation, and evaluation of an AI-driven mobile application for rare disease support [1]. Rare diseases are often misdiagnosed, with high costs and limited awareness restricting access to proper care. Our system addresses these issues through four components: an AI Doctor that answers medical queries, a networking module that locates hospitals and experts, a genetic testing feature that supports result uploads and scheduling, and a research hub that simplifies scientific findings [2]. We conducted an accurate experiment with 20 queries, achieving an 85% correct response rate and consistent disclaimers for safety. A comparison with related research showed our system to be more patient-centered, bilingual, and accessible than data-intensive clinical tools. While challenges remain in ensuring accuracy and privacy, the project demonstrates that AI can play a valuable role in bridging information gaps for rare disease patients, offering practical, accessible support beyond traditional healthcare systems.

AI health app, Rare disease support, Medical query system, Patient-centered care