“Auditing the inference processes of medical-image classifiers by leveraging generative AI and the expertise of physicians” by Roxana Daneshjou (et all) was featured on the latest cover of Nature Biomedical Engineering.
Abtract: The inferences of most machine-learning models powering medical artificial intelligence are difficult to interpret. Here we report a general framework for model auditing that combines insights from medical experts with a highly expressive form of explainable artificial intelligence. Specifically, we leveraged the expertise of dermatologists for the clinical task of differentiating melanomas from melanoma ‘lookalikes’ on the basis of dermoscopic and clinical images of the skin, and the power of generative models to render ‘counterfactual’ images to understand the ‘reasoning’ processes of five medical-image classifiers.
Read it here:
https://www.nature.com/natbiomedeng/volumes/9/issues/3#NewsandViews
Congratulations, Roxana!
