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[HTML][HTML] Machine learning–enabled clinical information systems using fast healthcare interoperability resources data standards: sco** review
Background Machine learning–enabled clinical information systems (ML-CISs) have the
potential to drive health care delivery and research. The Fast Healthcare Interoperability …
potential to drive health care delivery and research. The Fast Healthcare Interoperability …
Machine learning–based prediction models for delirium: a systematic review and meta-analysis
Q ** review of inpatient delirium prediction models
Objectives Early identification of inpatients at risk of develo** delirium and implementing
preventive measures could avoid up to 40% of delirium cases. Machine learning (ML)-based …
preventive measures could avoid up to 40% of delirium cases. Machine learning (ML)-based …
Artificial intelligence predicts delirium following cardiac surgery: A case study
J Fliegenschmidt, N Hulde, MG Preising… - Journal of clinical …, 2021 - Elsevier
Delirium is a highly relevant complication of surgical interventions. Current research
indicates that despite increased awareness for delirium, it is often overlooked. We …
indicates that despite increased awareness for delirium, it is often overlooked. We …
[HTML][HTML] Delirium screening in an acute care setting with a machine learning classifier based on routinely collected nursing data: a model development study
TR Spiller, E Tufan, H Petry, S Böttger, S Fuchs… - Journal of Psychiatric …, 2022 - Elsevier
Delirium screening in acute care settings is a resource intensive process with frequent
deviations from screening protocols. A predictive model relying only on daily collected …
deviations from screening protocols. A predictive model relying only on daily collected …