2026-06-29T07:30:34Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/723912023-08-25T13:16:20Zcom_20.500.14352_14col_20.500.14352_15

Efficacy of a Deep Learning Convolutional Neural Network System for Melanoma Diagnosis in a Hospital Population Martin Gonzalez, Manuel Azcárraga Llobet, Carlos Martín Gil, Alba Carpena Torres, Carlos Jaén Olasolo, Pedro 616-006.04:616.5 616.5-006.81-07 melanoma skin cancer oncology artificial intelligence deep learning Dermatología Oncología Técnicas de la imagen 3201.06 dermatología 3201.01 Oncología The purpose of this study was to evaluate the efficacy in terms of sensitivity, specificity, and accuracy of the quantusSKIN system, a new clinical tool based on deep learning, to distinguish between benign skin lesions and melanoma in a hospital population. (2) Methods: A retrospective study was performed using 232 dermoscopic images from the clinical database of the Ramón y Cajal University Hospital (Madrid, Spain). The skin lesions images, previously diagnosed as nevus (n = 177) or melanoma (n = 55), were analyzed by the quantusSKIN system, which offers a probabilistic percentage (diagnostic threshold) for melanoma diagnosis. The optimum diagnostic threshold, sensitivity, specificity, and accuracy of the quantusSKIN system to diagnose melanoma were quantified. (3) Results: The mean diagnostic threshold was statistically lower (p < 0.001) in the nevus group (27.12 ± 35.44%) compared with the melanoma group (72.50 ± 34.03%). The area under the ROC curve was 0.813. For a diagnostic threshold of 67.33%, a sensitivity of 0.691, a specificity of 0.802, and an accuracy of 0.776 were obtained. (4) Conclusions: The quantusSKIN system is proposed as a useful screening tool for melanoma detection to be incorporated in primary health care systems. Depto. de Optometría y Visión Fac. de Óptica y Optometría TRUE pub 2023-06-22T11:24:39Z 2023-06-22T11:24:39Z 2022-03-24 journal article https://hdl.handle.net/20.500.14352/72391 1660-4601 10.3390/ijerph19073892 eng open access application/pdf MDPI