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

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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Bibliographic Details
Main Authors: Kambiz Kamyab-Hesari, Vahidehsadat Azhari, Ali Ahmadzade, Fahimeh Asadi Amoli, Anahita Najafi, Alireza Hasanzadeh, Alireza Beikmarzehei
Format: Article
Language:English
Published: BMC 2023-08-01
Series:Diagnostic Pathology
Subjects:
Sebaceous hyperplasia
Sebaceoma
Sebaceous adenoma
Sebaceous carcinoma
Sebaceous neoplasms
Online Access:https://doi.org/10.1186/s13000-023-01378-w

Internet

https://doi.org/10.1186/s13000-023-01378-w

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