Machine learning model combining features from algorithms with different analytical methodologies to detect laboratory-event-related adverse drug reaction signals

BACKGROUND: The importance of identifying and evaluating adverse drug reactions (ADRs) has been widely recognized. Many studies have developed algorithms for ADR signal detection using electronic health record (EHR) data. In this study, we propose a machine learning (ML) model that enables accurate...

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Detalles Bibliográficos
Autores principales: Jeong, Eugene, Park, Namgi, Choi, Young, Park, Rae Woong, Yoon, Dukyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6248973/
https://www.ncbi.nlm.nih.gov/pubmed/30462745
http://dx.doi.org/10.1371/journal.pone.0207749

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6248973/
https://www.ncbi.nlm.nih.gov/pubmed/30462745
http://dx.doi.org/10.1371/journal.pone.0207749

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