This paper is in the following e-collection/theme issue:

Digital Health Reviews (1801) Artificial Intelligence (2295) Image Recognition and AI in Dermatology (22) Machine Learning from Digital Images in Dermatology (17) Cancer Prognosis Models and Machine Learning (75) Innovations in Cancer Diagnostic and Decision Support (120) Decision Support for Health Professionals (1612) Imaging Informatics (322)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73541, first published .
Deep Learning Algorithms in the Diagnosis of Basal Cell Carcinoma Using Dermatoscopy: Systematic Review and Meta-Analysis

Deep Learning Algorithms in the Diagnosis of Basal Cell Carcinoma Using Dermatoscopy: Systematic Review and Meta-Analysis

Deep Learning Algorithms in the Diagnosis of Basal Cell Carcinoma Using Dermatoscopy: Systematic Review and Meta-Analysis

Authors of this article:

Huasheng Liu1, 2 Author Orcid Image ;   Guangqian Shang3 Author Orcid Image ;   Qianqian Shan4 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Daneshi K, Neocleous Y, G-Medhin A, Gokani V. An educational machine learning demonstration framework for plastic surgeons using open datasets. Journal of Plastic, Reconstructive & Aesthetic Surgery 2026;115:89 View

Conference Proceedings

  1. P K, R G, S C, L S. 2025 5th International Conference on Evolutionary Computing and Mobile Sustainable Networks (ICECMSN). SkinScanNet Deep Learning Framework for Early Detection of Skin Cancer from Dermoscopic Images View