Sepsis prediction, early detection, and identification using clinical text for machine learning: a systematic review

OBJECTIVE: To determine the effects of using unstructured clinical text in machine learning (ML) for prediction, early detection, and identification of sepsis. MATERIALS AND METHODS: PubMed, Scopus, ACM DL, dblp, and IEEE Xplore databases were searched. Articles utilizing clinical text for ML or nat...

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Detalles Bibliográficos
Autores principales: Yan, Melissa Y, Gustad, Lise Tuset, Nytrø, Øystein
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8800516/
https://www.ncbi.nlm.nih.gov/pubmed/34897469
http://dx.doi.org/10.1093/jamia/ocab236

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8800516/
https://www.ncbi.nlm.nih.gov/pubmed/34897469
http://dx.doi.org/10.1093/jamia/ocab236

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