J Drugs Dermatol. 2022 Feb 1;21(2):191-194. doi: 10.36849/jdd.6277.
ABSTRACT
BACKGROUND: Background: Early detection of malignant skin lesions reduces morbidity. There is increased need for a telemedicine triage tool to prioritize patients who require in-person evaluation for potential malignancy.
OBJECTIVE: To evaluate the utility of artificial intelligence (AI) in telemedicine triage and diagnosis of cutaneous lesions.
METHODS: Clinical photographs of unbiopsied skin lesions were presented to AI software and three board-certified dermatologists with 18 years average clinical experience. Diagnoses were compared with biopsy reports of the same lesions.
RESULTS: Results from 100 images revealed no significant diagnostic difference between AI and a panel of three dermatologists when using the AI top three differential diagnoses. The AI correctly identified 63% of the cases whereas the dermatology group correctly identified 64.3% of the cases (P<.05). In summary, there was no statistically significant difference when evaluating lesions.
CONCLUSION: The use of artificial intelligence as a method of triaging patients with potential skin cancer is a very useful option in telemedicine, as AI identification of BCC, SCC, and melanoma did not significantly differ from board-certified dermatologists. Both dermatologists and non-dermatologists will benefit from an AI triage system, prioritizing lesions that the software deems malignant. J Drugs Dermatol. 2022;21(2):191-194. doi:10.36849/JDD.6277.
PMID:35133107 | DOI:10.36849/jdd.6277