Advancing NSCLC pathological subtype prediction with interpretable machine learning: a comprehensive radiomics-based approach

ObjectiveThis research aims to develop and assess the performance of interpretable machine learning models for diagnosing three histological subtypes of non-small cell lung cancer (NSCLC) utilizing CT imaging data.MethodsA retrospective cohort of 317 patients diagnosed with NSCLC was included in the...

ver descrição completa

Detalhes bibliográficos

Principais autores:	Bingling Kuang, Jingxuan Zhang, Mingqi Zhang, Haoming Xia, Guangliang Qiang, Jiangyu Zhang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2024-05-01
Colecção:	Frontiers in Medicine
Assuntos:	histological subtype non-small cell lung cancer interpretable machine learning CT radiomics
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fmed.2024.1413990/full
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!