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

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-sectional stu...

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Detalles Bibliográficos
Autores principales: Kamyab-Hesari, Kambiz, Azhari, Vahidehsadat, Ahmadzade, Ali, Asadi Amoli, Fahimeh, Najafi, Anahita, Hasanzadeh, Alireza, Beikmarzehei, Alireza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10405381/
https://www.ncbi.nlm.nih.gov/pubmed/37550731
http://dx.doi.org/10.1186/s13000-023-01378-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10405381/
https://www.ncbi.nlm.nih.gov/pubmed/37550731
http://dx.doi.org/10.1186/s13000-023-01378-w

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