Enabling Data-Driven Clinical Quality Assurance: Predicting Adverse Event Reporting in Clinical Trials Using Machine Learning

INTRODUCTION: Adverse event (AE) under-reporting has been a recurrent issue raised during health authorities Good Clinical Practices (GCP) inspections and audits. Moreover, safety under-reporting poses a risk to patient safety and data integrity. The current clinical Quality Assurance (QA) practices...

Descripción completa

Detalles Bibliográficos
Autores principales: Ménard, Timothé, Barmaz, Yves, Koneswarakantha, Björn, Bowling, Rich, Popko, Leszek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6689279/
https://www.ncbi.nlm.nih.gov/pubmed/31123940
http://dx.doi.org/10.1007/s40264-019-00831-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6689279/
https://www.ncbi.nlm.nih.gov/pubmed/31123940
http://dx.doi.org/10.1007/s40264-019-00831-4

Ejemplares similares