Development of a pharmaceutical science systematic review process using a semi‐automated machine learning tool: Intravenous drug compatibility in the neonatal intensive care setting

Development of a pharmaceutical science systematic review process using a semi‐automated machine learning tool: Intravenous drug compatibility in the neonatal intensive care setting

Abstract Our objective was to establish and test a machine learning‐based screening process that would be applicable to systematic reviews in pharmaceutical sciences. We used the SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, Research type) model, a broad search strategy, and a machine...

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Detalles Bibliográficos
Main Authors: D. Thisuri N. De Silva, Brioni R. Moore, Tobias Strunk, Michael Petrovski, Vanessa Varis, Kevin Chai, Leo Ng, Kevin T. Batty
Formato: Artigo
Idioma:English
Publicado: Wiley 2024-02-01
Series:Pharmacology Research & Perspectives
Subjects:
machine learning
pharmaceutical science
physicochemical compatibility
systematic review
Acceso en liña:https://doi.org/10.1002/prp2.1170

Internet

https://doi.org/10.1002/prp2.1170

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