Problems and Potentials of Automated Object Detection for Skin Cancer Recognition
Author:
Affiliation:
1. Department of Dermatology, Medical University of Vienna, Vienna, Austria
Publisher
American Medical Association (AMA)
Subject
Dermatology
Link
https://jamanetwork.com/journals/jamadermatology/articlepdf/2756344/jamadermatology_tschandl_2019_ed_190030.pdf
Reference9 articles.
1. Dermatologist-level classification of skin cancer with deep neural networks.;Esteva;Nature,2017
2. Classification of the clinical images for benign and malignant cutaneous tumors using a deep learning algorithm.;Han;J Invest Dermatol,2018
3. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.;Haenssle;Ann Oncol,2018
4. Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study.;Tschandl;Lancet Oncol,2019
5. Keratinocytic skin cancer detection on the face using region-based convolutional neural network;Han;JAMA Dermatol
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