activity
20222026
most citedToward Fairness Through Fair Multi-Exit Framework for Dermatological Disease Diagnosis

12 citations · 41 across the 7 of their papers we have counts for

collaborators

8 papers

cs.AI2026

CRC-Router: Risk-Constrained Routing for Medical Agentic AI Systems

Xueyang Li, Mingze Jiang, Gelei Xu +5

Agentic AI systems are increasingly being explored in medical imaging to improve throughput and reduce clinician workload; however, safe deployment remains challenging because auto…

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.CV2024

Achieving Fairness Through Channel Pruning for Dermatological Disease Diagnosis

Qingpeng Kong, Ching-Hao Chiu, Dewen Zeng +4

Numerous studies have revealed that deep learning-based medical image classification models may exhibit bias towards specific demographic attributes, such as race, gender, and age.…

cs.CV2024

Toward Fairness via Maximum Mean Discrepancy Regularization on Logits Space

Hao-Wei Chung, Ching-Hao Chiu, Yu-Jen Chen +2

Fairness has become increasingly pivotal in machine learning for high-risk applications such as machine learning in healthcare and facial recognition. However, we see the deficienc…

cs.CV2024★ 11 cited

Achieve Fairness without Demographics for Dermatological Disease Diagnosis

Ching-Hao Chiu, Yu-Jen Chen, Yawen Wu +2

In medical image diagnosis, fairness has become increasingly crucial. Without bias mitigation, deploying unfair AI would harm the interests of the underprivileged population and po…

cs.CV2023★ 12 cited

Toward Fairness Through Fair Multi-Exit Framework for Dermatological Disease Diagnosis

Ching-Hao Chiu, Hao-Wei Chung, Yu-Jen Chen +2

Fairness has become increasingly pivotal in medical image recognition. However, without mitigating bias, deploying unfair medical AI systems could harm the interests of underprivil…

cs.CV2023★ 6 cited

Fair Multi-Exit Framework for Facial Attribute Classification

Ching-Hao Chiu, Hao-Wei Chung, Yu-Jen Chen +2

Fairness has become increasingly pivotal in facial recognition. Without bias mitigation, deploying unfair AI would harm the interest of the underprivileged population. In this pape…

cs.CV2022★ 12 cited

Representative Image Feature Extraction via Contrastive Learning Pretraining for Chest X-ray Report Generation

Yu-Jen Chen, Wei-Hsiang Shen, Hao-Wei Chung +6

Medical report generation is a challenging task since it is time-consuming and requires expertise from experienced radiologists. The goal of medical report generation is to accurat…