01297nas a2200157   4500000000100000008004100001260000900042653001800051653000800069100001600077700001400093700001000107700001400117245010100131520090700232       2024                            d  bIEEE10aDeep Learning10aNTD1 aPattnayak P1 aMohanty A1 aDas T1 aPatnaik S00aApplying Artificial Intelligence and Deep Learning to Identify Neglected Tropical Skin Disorders3 a<p>Visual inspection plays a significant role in the identification of skin diseases, albeit it is not the only method. Teledermatology techniques are thus particularly suitable for the diagnosis and treatment of these disorders. In vision tasks, deep learning (DL), a subset of machine learning (ML) and/or artificial intelligence (AI), has produced outstanding results. There has been few research in this field, and even fewer that have focused on dark skin, despite the growing interest in using this technology to improve diagnostics for neglected tropical diseases affecting the skin (skin NTDs). In this work, we used clinical photos to create AI models based on deep learning. In order to determine whether or not various models with training patterns can increase diagnosis accuracy. The five skin NTDs in which data were gathered were yaws, scabies, mycetoma, leprosy, and Buruli ulcer.</p>