Performance of Artificial Intelligence in Skin Cancer Detection: An Umbrella Review of Systematic Reviews and Meta‐Analyses

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Umbrella review synthesizes meta-analyses on AI diagnostic accuracy in skin cancer, highlighting statistically significant performance metrics.

AI models demonstrate high diagnostic accuracy for skin cancer, with convolutional neural networks leading in performance.
Sensitivity and specificity for melanoma diagnosis reached 91% and 94% respectively, outperforming junior dermatologists.
Machine learning models trained on hyperspectral imaging achieved a sensitivity of 90.1% for squamous cell carcinoma detection.
Integrating AI tools in primary care can enhance diagnostic accuracy, benefiting generalists and nurse practitioners significantly.

Karimzadhagh et al. (2025) studied this question.

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Umbrella review synthesizes meta-analyses on AI diagnostic accuracy in skin cancer, highlighting statistically significant performance metrics.