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Basic Elements of Artificial Intelligence Tools in the Diagnosis of Cutaneous Melanoma
Giulia Querzoli1, Giulia Veronesi2, Barbara Corti1
1Pathology Unit, IRCCS Azienda Ospedaliero Universitaria di Bologna, Italy.
Abstract:
Cutaneous melanoma (CM) incidence has dramatically increased in the last years. Early diagnosis is of paramount importance in terms of prognosis. Artificial Intelligence (AI) tools are being proposed for clinicians and pathologists as an adjunct support in the diagnostic process. We described herein an overview of the most important parameters that a potential AI tool should take into consideration in histopathology to evaluate a skin lesion. First of all, recognition of a melanocytic or non-melanocytic nature. Furthermore, melanocytic lesions should be stratified according to at least four parameters: silhouette and asymmetry; identification and spatial distribution of the cells; mitosis count; presence of ulceration. According to the number of parameters the AI tools might stratify the risk of CM and prioritize the pathologist's work.

