Deep learning for disease diagnosis confounded by image labels – Physics World

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Artificial intelligence (AI) has potential to play a pivotal role in many areas of medicine. In particular, the use of deep learning to analyse medical images and improve the accuracy of disease diagnosis is a rapidly growing area of interest. But AI is not perfect. A new study has revealed that radiograph labels can confuse AI networks and limit their clinical utility. The problem arises due to a phenomenon called hidden stratification, in which convolutional neural networks (CNN) trained to analyse medical images learn to classify the image based on diagnostically irrelevant features.

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