"Combining Automated Lesion Risk and Change Assessment Improves Melanoma Detection: A Retrospective Accuracy Study" Featured on Journal of Investigative Dermatology
Artificial intelligence (AI) in dermatology has high accuracy in classifying skin cancer, particularly in collaboration with dermatologists. Although clinical studies have evaluated AI tools on both single-timepoint lesion images and sequential imaging data, they lack reporting on clinical utility in real-world settings. We retrospectively evaluate performances of 2 AI models for lesion change and malignancy risk assessment.
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