A Risk-Factor Model for Antineoplastic Drug-Induced Serious Adverse Events in Cancer Inpatients: A Retrospective Study Based on the Global Trigger Tool and Machine Learning

The objective of this study was to apply a machine learning method to evaluate the risk factors associated with serious adverse events (SAEs) and predict the occurrence of SAEs in cancer inpatients using antineoplastic drugs. A retrospective review of the medical records of 499 patients diagnosed wi...

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Detalles Bibliográficos
Autores principales: Zhang, Ni, Pan, Ling-Yun, Chen, Wan-Yi, Ji, Huan-Huan, Peng, Gui-Qin, Tang, Zong-Wei, Wang, Hui-Lai, Jia, Yun-Tao, Gong, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Pharmacology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9277092/
https://www.ncbi.nlm.nih.gov/pubmed/35847000
http://dx.doi.org/10.3389/fphar.2022.896104

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9277092/
https://www.ncbi.nlm.nih.gov/pubmed/35847000
http://dx.doi.org/10.3389/fphar.2022.896104

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