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Data Safety: Synthetic Data Quality Analysis Using CIFAKE Dataset
Kuniko Paxton, Amila Akagić, Koorosh Aslansefat +2
Recently, the societal implementation of high-performance image classification models has expanded rapidly. While these models require vast amounts of training data to improve perf…
Exploring the Impact of Skin Color on Skin Lesion Segmentation
Kuniko Paxton, Medina Kapo, Amila Akagić +3
Skin cancer, particularly melanoma, remains a major cause of morbidity and mortality, making early detection critical. AI-driven dermatology systems often rely on skin lesion segme…
Skewness-Guided Pruning of Multimodal Swin Transformers for Federated Skin Lesion Classification on Edge Devices
Kuniko Paxton, Koorosh Aslansefat, Dhavalkumar Thakker +1
In recent years, high-performance computer vision models have achieved remarkable success in medical imaging, with some skin lesion classification systems even surpassing dermatolo…
Mitigating Individual Skin Tone Bias in Skin Lesion Classification through Distribution-Aware Reweighting
Kuniko Paxton, Zeinab Dehghani, Koorosh Aslansefat +2
Skin color has historically been a focal point of discrimination, yet fairness research in machine learning for medical imaging often relies on coarse subgroup categories, overlook…
Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learning
Kuniko Paxton, Koorosh Aslansefat, Dhavalkumar Thakker +2
Recent advances in deep learning have significantly improved the accuracy of skin lesion classification models, supporting medical diagnoses and promoting equitable healthcare. How…
Safer Skin Lesion Classification with Global Class Activation Probability Map Evaluation and SafeML
Kuniko Paxton, Koorosh Aslansefat, Amila Akagić +2
Recent advancements in skin lesion classification models have significantly improved accuracy, with some models even surpassing dermatologists' diagnostic performance. However, in…