11 citations · 11 across the 3 of their papers we have counts for
5 papers · 1 filter
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…
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.…
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…
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…
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…