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Toward Fairness via Maximum Mean Discrepancy Regularization on Logits Space
Fairness has become increasingly pivotal in machine learning for high-risk applications such as machine learning in healthcare and facial recognition.
Achieve Fairness without Demographics for Dermatological Disease Diagnosis
To overcome this, we propose a method enabling fair predictions for sensitive attributes during the testing phase without using such information during training.
Toward Fairness Through Fair Multi-Exit Framework for Dermatological Disease Diagnosis
Fairness has become increasingly pivotal in medical image recognition.
Fair Multi-Exit Framework for Facial Attribute Classification
Fairness has become increasingly pivotal in facial recognition.
Representative Image Feature Extraction via Contrastive Learning Pretraining for Chest X-ray Report Generation
Medical report generation is a challenging task since it is time-consuming and requires expertise from experienced radiologists.
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