Predictive modeling of clinical trial terminations using feature engineering and embedding learning

Abstract In this study, we propose to use machine learning to understand terminated clinical trials. Our goal is to answer two fundamental questions: (1) what are common factors/markers associated to terminated clinical trials? and (2) how to accurately predict whether a clinical trial may be termin...

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Autores principales: Magdalyn E. Elkin, Xingquan Zhu
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/6f7430ca29734e37a28ff3887950ba2e
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