Article

Ensemble uncertainty estimation improves skin cancer malignancy prediction

2025-08-24

Abstract excerpt

Widespread access to imaging technologies and stronger machine learning (ML) architectures for dermatology tasks such as malignancy prediction have spurred a race to develop models to assist in the automated diagnosis of skin cancer. However, high diagnostic performance on benchmarking datasets quickly deteriorates when models are challenged with data from disparate clinical sources. Generalization gaps stem from...

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Literature Corpus work: 0675e465-32d5-5e91-ba7e-c9d923c9a4fd
DOI: 10.1101/2025.08.20.25334101

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