Multi-task learning-based feature selection and classification models for glioblastoma and solitary brain metastases

PURPOSE: To investigate the diagnostic performance of feature selection via a multi-task learning model in distinguishing primary glioblastoma from solitary brain metastases. METHOD: The study involved 187 patients diagnosed at Xiangya Hospital, Yunnan Provincial Cancer Hospital, and Southern Cancer...

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Detalles Bibliográficos
Autores principales: Huang, Ya, Huang, Shan, Liu, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9533336/
https://www.ncbi.nlm.nih.gov/pubmed/36212457
http://dx.doi.org/10.3389/fonc.2022.1000471

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9533336/
https://www.ncbi.nlm.nih.gov/pubmed/36212457
http://dx.doi.org/10.3389/fonc.2022.1000471

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