[HTML][HTML] Machine learning–enabled clinical information systems using fast healthcare interoperability resources data standards: sco** review

JA Balch, MM Ruppert, TJ Loftus, Z Guan… - JMIR Medical …, 2023 - medinform.jmir.org
Background Machine learning–enabled clinical information systems (ML-CISs) have the
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
T Strating, LS Hanjani, I Tornvall… - BMJ Health & Care …, 2023 - pmc.ncbi.nlm.nih.gov
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 …

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 …

[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 …