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20222026
most citedAchieving Fairness in Dermatological Disease Diagnosis through Automatic Weight Adjusting Federated Learning and Personalization

5 citations · 5 across the 14 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

cs.CV2026

Text Over Image: Auditing Multimodal Robustness in Synthetic Medical Image Detection

Ching-Hao Chiu, Hao-Wei Chung, Gelei Xu +7

With the rapid adoption of generative AI, synthetic medical images pose growing risks, including diagnostic deception and insurance fraud. Although prior work has explored vision-l…

cs.CV2026

MORI-Seg: Learning Morphological Geometry for Instance Segmentation without Instance Annotations

Leiyue Zhao, Tianyu Shi, Daniel Reisenbuchler +12

Instance-level quantification of kidney functional units is essential for morphometric analysis, yet most publicly available pathology datasets provide only semantic segmentation a…

cs.AI2026

An Empirical Study of Agent Skills for Healthcare: Practice, Gaps, and Governance

Gelei Xu, Ningzhi Tang, Xueyang Li +4

Healthcare automation is shaped by local procedures and organizational constraints, so agent capabilities rarely transfer unchanged across settings. Agent skills, self-contained di…

cs.SE2026

How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions

Ningzhi Tang, Chaoran Chen, Gelei Xu +5

AI coding agents increasingly act directly within software environments, yet existing analyses of their failures rely on benchmark trajectories that miss how developers actually ex…

cs.SE2026

Programming by Chat: A Large-Scale Behavioral Analysis of 11,579 Real-World AI-Assisted IDE Sessions

Ningzhi Tang, Chaoran Chen, Zihan Fang +6

IDE-integrated AI coding assistants, which operate conversationally within developers' working codebases with access to project context and multi-file editing, are rapidly reshapin…

cs.CV2026

Patient-Conditioned Adaptive Offsets for Reliable Diagnosis across Subgroups

Gelei Xu, Yuying Duan, Jun Xia +3

AI models for medical diagnosis often exhibit uneven performance across patient populations due to heterogeneity in disease prevalence, imaging appearance, and clinical risk profil…