Leveraging machine learning techniques for predicting pancreatic neuroendocrine tumor grades using biochemical and tumor markers

BACKGROUND: The incidence of pancreatic neuroendocrine tumors (PNETs) is now increasing rapidly. The tumor grade of PNETs significantly affects the treatment strategy and prognosis. However, there is still no effective way to non-invasively classify PNET grades. Machine learning (ML) algorithms have...

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Detalles Bibliográficos
Autores principales: Zhou, Rui-Quan, Ji, Hong-Chen, Liu, Qu, Zhu, Chun-Yu, Liu, Rong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2019
Materias:
Retrospective Study
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6658377/
https://www.ncbi.nlm.nih.gov/pubmed/31367620
http://dx.doi.org/10.12998/wjcc.v7.i13.1611

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6658377/
https://www.ncbi.nlm.nih.gov/pubmed/31367620
http://dx.doi.org/10.12998/wjcc.v7.i13.1611

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