collaborators

5 papers

cs.AI2026

Data-Driven Analysis of AI in Medical Device Software in China: Trends of Deep Learning and Traditional AI Based on Regulatory Data

Yu Han, Aaron Ceross, Sarim Ather +1

Artificial intelligence (AI) in medical device software (MDSW) represents a transformative clinical technology, attracting increasing attention within both the medical community an…

eess.SY2026

Measuring Cross-Jurisdictional Transfer of Medical Device Risk Concepts with Explainable AI

Yu Han, Aaron Ceross

Medical device regulators in the United States(FDA), China (NMPA), and Europe (EU MDR) all use the language of risk, but classify devices through structurally different mechanisms.…

cs.AI2025

Standard Applicability Judgment and Cross-jurisdictional Reasoning: A RAG-based Framework for Medical Device Compliance

Yu Han, Aaron Ceross, Jeroen H. M. Bergmann

Identifying the appropriate regulatory standard applicability remains a critical yet understudied challenge in medical device compliance, frequently necessitating expert interpreta…

cs.AI2025

AI for Regulatory Affairs: Balancing Accuracy, Interpretability, and Computational Cost in Medical Device Classification

Yu Han, Aaron Ceross, Jeroen H. M. Bergmann

Regulatory affairs, which sits at the intersection of medicine and law, can benefit significantly from AI-enabled automation. Classification task is the initial step in which manuf…

cs.LG2025

Toward Automated Regulatory Decision-Making: Trustworthy Medical Device Risk Classification with Multimodal Transformers and Self-Training

Yu Han, Aaron Ceross, Jeroen H. M. Bergmann

Accurate classification of medical device risk levels is essential for regulatory oversight and clinical safety. We present a Transformer-based multimodal framework that integrates…