Artificial Intelligence in Melanoma Dermatopathology: A Review of Literature
- PMID: 37982502
- DOI: 10.1097/DAD.0000000000002593
Artificial Intelligence in Melanoma Dermatopathology: A Review of Literature
Abstract
Pathology serves as a promising field to integrate artificial intelligence into clinical practice as a powerful screening tool. Melanoma is a common skin cancer with high mortality and morbidity, requiring timely and accurate histopathologic diagnosis. This review explores applications of artificial intelligence in melanoma dermatopathology, including differential diagnostics, prognosis prediction, and personalized medicine decision-making.
Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.
Conflict of interest statement
The authors declare no conflicts of interest.
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References
-
- Muehlematter UJ, Daniore P, Vokinger KN. Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis. Lancet Digit Health. 2021;3:e195–e203.
-
- Krizhevsky A, Sutskever I, Hinton GE. ImageNet classification with deep convolutional neural networks. Commun ACM. 2017;60:84–90.
-
- Sultan AS, Elgharib MA, Tavares T, et al. The use of artificial intelligence, machine learning and deep learning in oncologic histopathology. J Oral Pathol Med. 2020;49:849–856.
-
- Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019;69:7–34.
-
- Bolick NL, Geller AC. Epidemiology of melanoma. Hematol Oncol Clin North Am. 2021;35:57–72.
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