Papachristou et al. examines the use of AI and its role in detecting skin cancers. In comparison to dermatologists, the question regarding its accuracy in a clinical setting is currently being evaluated. This study specifically evaluated the performance of a smartphone app, Dermalyser, for melanoma detection, which was conducted across 36 Sweden primary care centers. 228 patients and 253 skin lesions were assessed with an identification of 21 melanomas. Each lesion was exposed to standard diagnostic procedures such as biopsy and histopathology to ensure consistency. Then, the final clinical diagnoses were compared to the results determined by the app. The findings revealed that the app had high diagnostic accuracy of 0.960 AUROC, with a sensitivity of 95.2% and specificity of 84.5%. Regarding the most invasive melanomas, the AUROC was 0.988 and reached 100% sensitivity and 92.6% specificity. Additionally, there was a 99.5% probability that the lesion was benign if the app detected no melanoma. Overall, this study highlights the potential for high diagnostic accuracy within a clinical setting where potential benefits of a smartphone app can reduce errors and increase efficiency. The possibility of reducing unnecessary excisions and allow early melanoma detection brings light to the intersection between AI and clinical decision-making in dermatology.