- •Specific characteristics of automated skin lesion detection make technology valuable and scalable.
- •Ideal clinical use would accommodate both standardized and nonstandardized photos.
- •A one-system model decision support tool needs clinical validation and robust training.
Contextual learning in lesion classification
Nonstandardized and standardized input in AI classification
Models with robust training and clinical validation: When do we make it public?
Conflict of Interest
- Gender shades: Intersectional accuracy disparities in commercial gender classification. In: Conference on Fairness.Accountability and Transparency. 21 January 2018; : 77-91
- Dermatologist-level classification of skin cancer with deep neural networks.Nature. 2017; 542: 115
- Classification of the clinical images for benign and malignant cutaneous tumors using a deep learning algorithm.J Invest Dermatol. 2018; 138: 1529-1538
- AUC: a better measure than accuracy in comparing learning algorithms.in: Conference of the Canadian Society for Computational Studies of Intelligence. Springer, Berlin, Heidelberg11 June 2003: 329-341
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