Combining artificial intelligence and human expertise for more accurate dermoscopic melanoma diagnosis: A 2-session retrospective reader study

J Am Acad Dermatol. 2024 Jun;90(6):1266-1268. doi: 10.1016/j.jaad.2023.12.072. Epub 2024 Feb 29.

Affiliations

¹ Department of Dermatology, University Medical Center Mainz, Mainz, Germany.
² Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut.
³ Department of Dermatology, University Medical Center Mainz, Mainz, Germany. Electronic address: Stephan.Grabbe@unimedizin-mainz.de.
⁴ Aigora GmbH, Munich, Germany.
⁵ Department of Dermatology, Bangalore Medical College and Research Institute, Bengaluru, India.

PMID: 38430100
DOI: 10.1016/j.jaad.2023.12.072

No abstract available

Keywords: artificial intelligence; convolutional neural networks; dermoscopic diagnostics; melanoma; nevi; skin cancer.

Publication types

Letter

MeSH terms

Artificial Intelligence*
Clinical Competence
Dermoscopy*
Humans
Melanoma* / diagnosis
Melanoma* / pathology
Retrospective Studies
Skin Neoplasms* / diagnosis
Skin Neoplasms* / pathology