Evaluating the Feasibility of Machine-Learning-Based Predictive Models for Precancerous Cervical Lesions in Patients Referred for Colposcopy

Background: Colposcopy plays an essential role in cervical cancer control, but its performance remains unsatisfactory. This study evaluates the feasibility of machine learning (ML) models for predicting high-grade squamous intraepithelial lesions or worse (HSIL+) in patients referred for colposcopy...

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Detalles Bibliográficos
Autores principales: Chen, Mingyang, Wang, Jiaxu, Xue, Peng, Li, Qing, Jiang, Yu, Qiao, Youlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9776471/
https://www.ncbi.nlm.nih.gov/pubmed/36553073
http://dx.doi.org/10.3390/diagnostics12123066

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9776471/
https://www.ncbi.nlm.nih.gov/pubmed/36553073
http://dx.doi.org/10.3390/diagnostics12123066

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