Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study

INTRODUCTION: Adverse drug events (ADEs) are associated with poor outcomes and increased costs but may be prevented with prediction tools. With the National Institute of Health All of Us (AoU) database, we employed machine learning (ML) to predict selective serotonin reuptake inhibitor (SSRI)-associ...

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Detalles Bibliográficos
Autores principales: Goyal, Jatin, Ng, Ding Quan, Zhang, Kevin, Chan, Alexandre, Lee, Joyce, Zheng, Kai, Hurley-Kim, Keri, Nguyen, Lee, He, Lu, Nguyen, Megan, McBane, Sarah, Li, Wei, Cadiz, Christine Luu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10257821/
https://www.ncbi.nlm.nih.gov/pubmed/37301967
http://dx.doi.org/10.1186/s12911-023-02206-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10257821/
https://www.ncbi.nlm.nih.gov/pubmed/37301967
http://dx.doi.org/10.1186/s12911-023-02206-3

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