Investigating the quality of dermamnist and fitzpatrick17k dermatological image datasets

K Abhishek, A Jain, G Hamarneh - Scientific Data, 2025 - nature.com
The remarkable progress of deep learning in dermatological tasks has brought us closer to
achieving diagnostic accuracies comparable to those of human experts. However, while …

Achieving Fairness Through Channel Pruning for Dermatological Disease Diagnosis

Q Kong, CH Chiu, D Zeng, YJ Chen, TY Ho… - … Conference on Medical …, 2024 - Springer
Numerous studies have revealed that deep learning-based medical image classification
models may exhibit bias towards specific demographic attributes, such as race, gender, and …

Toward Fairness via Maximum Mean Discrepancy Regularization on Logits Space

HW Chung, CH Chiu, YJ Chen, Y Shi, TY Ho - arxiv preprint arxiv …, 2024 - arxiv.org
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 …

Evaluating Fairness and Mitigating Bias in Machine Learning: A Novel Technique using Tensor Data and Bayesian Regression

K Paxton, K Aslansefat, D Thakker, Y Papadopoulos - openreview.net
Fairness is a critical component of Trustworthy AI. In this paper, we focus on Machine
Learning (ML) and the performance of model predictions when dealing with skin color …