Machine learning for classification of cutaneous sebaceous neoplasms: implementing decision tree model using cytological and architectural features

Abstract Background This observational study aims to describe and compare histopathological, architectural, and nuclear characteristics of sebaceous lesions and utilized these characteristics to develop a predictive classification approach using machine learning algorithms. Methods This cross-sectio...

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Автори:	Kambiz Kamyab-Hesari, Vahidehsadat Azhari, Ali Ahmadzade, Fahimeh Asadi Amoli, Anahita Najafi, Alireza Hasanzadeh, Alireza Beikmarzehei
Формат:	Artigo
Мова:	Inglês
Опубліковано:	BMC 2023-08-01
Серія:	Diagnostic Pathology
Предмети:	Sebaceous hyperplasia Sebaceoma Sebaceous adenoma Sebaceous carcinoma Sebaceous neoplasms
Онлайн доступ:	https://doi.org/10.1186/s13000-023-01378-w
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