How Consistent is the Output of DERM, When Used to Assess Images of Potentially Cancerous Skin Lesions.

DERM is a Medical Device that uses artificial intelligence to help doctors check if a skin lesion might be cancerous. It works by analysing close-up pictures of skin lesions taken with a smartphone. This study aims to demonstrate how consistent (precise) the output of DERM is: i.e. does it provide the same result when it analyses multiple photos of the same lesion (repeatability), and when the same lesion is photographed by different people, or with different cameras (reproducibility). Adults with at least one skin lesion that doctors are checking for cancer, as part of their standard care, will be able to take part. Suitable lesions will be photographed three times, each by three different people using three sets of image capture hardware (specifically, an iPhone 11 with a DL200/HR dermoscopic lens). Each image will be checked for good image quality as it is captured. Images will then be transferred to DERM, where they'll be analysed. The DERM output won't be shared with the patients or doctors involved in the study. The patients will continue to have their skin lesion biopsy/excised, in accordance with standard of care. Their diagnosis will be collected and compared to the output from DERM.