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Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data

OBJECTIVE: In applying machine learning (ML) to electronic health record (EHR) data, many decisions must be made before any ML is applied; such preprocessing requires substantial effort and can be labor-intensive. As the role of ML in health care grows, there is an increasing need for systematic and...

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Detalhes bibliográficos
Publicado no:J Am Med Inform Assoc
Main Authors: Tang, Shengpu, Davarmanesh, Parmida, Song, Yanmeng, Koutra, Danai, Sjoding, Michael W, Wiens, Jenna
Formato: Artigo
Idioma:Inglês
Publicado em: Oxford University Press 2020
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7727385/
https://ncbi.nlm.nih.gov/pubmed/33040151
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocaa139
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