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Deep Learning in Dermatology: A Systematic Review of Current Approaches, Outcomes, and Limitations.


ABSTRACT: Artificial intelligence (AI) has recently made great advances in image classification and malignancy prediction in the field of dermatology. However, understanding the applicability of AI in clinical dermatology practice remains challenging owing to the variability of models, image data, database characteristics, and variable outcome metrics. This systematic review aims to provide a comprehensive overview of dermatology literature using convolutional neural networks. Furthermore, the review summarizes the current landscape of image datasets, transfer learning approaches, challenges, and limitations within current AI literature and current regulatory pathways for approval of models as clinical decision support tools.

SUBMITTER: Jeong HK 

PROVIDER: S-EPMC9841357 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Deep Learning in Dermatology: A Systematic Review of Current Approaches, Outcomes, and Limitations.

Jeong Hyeon Ki HK   Park Christine C   Henao Ricardo R   Kheterpal Meenal M  

JID innovations : skin science from molecules to population health 20220823 1


Artificial intelligence (AI) has recently made great advances in image classification and malignancy prediction in the field of dermatology. However, understanding the applicability of AI in clinical dermatology practice remains challenging owing to the variability of models, image data, database characteristics, and variable outcome metrics. This systematic review aims to provide a comprehensive overview of dermatology literature using convolutional neural networks. Furthermore, the review summ  ...[more]

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