Bias in Histopathology Datasets: A Comprehensive Investigation on Possible Factors
Farnaz Kheiri,
Shahryar Rahnamayan,
Masoud Makrehchi
et al.
Abstract:Deep Neural Networks (DNNs) have demonstrated remarkable capabilities in medical applications, including digital pathology, where they excel at analyzing complex patterns in medical images to assist in accurate disease diagnosis and prognosis. However, concerns have arisen about potential biases in The Cancer Genome Atlas (TCGA) dataset, a comprehensive repository for digitalized histopathology and a validation source for deep models, suggesting that over-optimistic results of model performance may be due to r… Show more
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