Automated Identification of Adults at Risk for In-Hospital Clinical Deterioration is a research paper published in New England Journal of Medicine (2020). On theSindex it has a DataRank of 0. It has been cited 293 times.
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Gordon and Betty Moore Foundation
Grant: 2663
Gordon and Betty Moore Foundation
Grant: 2663.01
National Institutes of Health
Grant: K23GM112018
National Institutes of Health
Grant: R35GM128672
Agency for Healthcare Research and Quality
Grant: 1R01HS018480-01
NLM NIH HHS
Grant: T15 LM007033
NCI NIH HHS
Grant: R25 CA180993
AHRQ HHS
Grant: R01 HS018480
The Permanente Medical Group, Inc.
Kaiser Foundation Hospitals, Inc.
Sidney Garfield Memorial Fund
FWCI
20.43
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Automated alert and activation of medical emergency team using early warning score
Additional file 1 of Automated alert and activation of medical emergency team using early warning score
Additional file 2 of Automated alert and activation of medical emergency team using early warning score
Additional file 2 of Automated alert and activation of medical emergency team using early warning score
Additional file 3 of Automated alert and activation of medical emergency team using early warning score
Additional file 3 of Automated alert and activation of medical emergency team using early warning score
Additional file 1 of Prospective evaluation of social risks, physical function, and cognitive function in prediction of non-elective rehospitalization and post-discharge mortality
Additional file 1 of Prospective evaluation of social risks, physical function, and cognitive function in prediction of non-elective rehospitalization and post-discharge mortality
Additional file 1 of The impact of changes in coding on mortality reports using the example of sepsis
Additional file 1 of The impact of changes in coding on mortality reports using the example of sepsis
Additional file 1 of Dynamic early warning scores for predicting clinical deterioration in patients with respiratory disease
Additional file 1 of Dynamic early warning scores for predicting clinical deterioration in patients with respiratory disease
Additional file 1 of Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare
Additional file 1 of Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare