Project Objectives and Expected Outcomes
This project aims to develop and validate an AI-assisted diabetic foot screening system that integrates image recognition, sensory testing, and pressure detection technology for early wound detection and neuropathy screening. The system is expected to reduce clinical screening burdens and establish a comprehensive foot health database, enabling remote monitoring applications to enhance diabetes health management.

Collaborative Partners and Project Duration
The project will collaborate with our university's Departments of Computer Science and Artificial Intelligence. U.S. students will be recruited to participate in a field study in Taiwan from February 1 to December 31, 2025.

Project Implementation
1. Technology Development and Testing: Students will be involved in programming, developing, and testing the accuracy of image recognition and pressure detection models.
2. Patient Data Identification Training: Workshops will be organized to teach data processing and image interpretation skills, enhancing students' ability to identify diabetic neuropathy indicators.
3. Internship Program: Students will participate in an internship at Chang Gung Memorial Hospital to collect foot images and sensory data and support clinical trial testing.
4. Database Construction and Application: A data integration and remote monitoring system will be established, simulating real-world application scenarios.

Funding Request
The project requests funding to cover the expenses of two students for a 2 months field study in Taiwan, providing each with a monthly stipend of NT$20,000 for living and tuition support.

Expected Outcomes
The project will produce a practical foot screening system and evaluate its clinical applicability, offering a viable AI solution for diabetic foot care, improving healthcare outcomes, and promoting the widespread adoption of AI in healthcare.