| Literature DB >> 28508776 |
Diether Kramer1, Sai Veeranki2, Dieter Hayn2, Franz Quehenberger3, Werner Leodolter1, Christian Jagsch1, Günter Schreier2.
Abstract
Delirium is an acute confusion condition, which is common in elderly and often misdiagnosed in hospitalized patients. Early identification and prevention of delirium could reduce morbidity and mortality rates in those affected and reduce hospitalization costs. We have developed and validated a multivariate prediction model that predicts delirium and gives an early warning to physicians. A large set of patient electronic medical records have been used in developing the models. Classical learning algorithms have been used to develop the models and compared the results. Excellent results were obtained with the feature set and parameter settings attaining accuracy of 84%.Entities:
Keywords: Delirium; electronic medical record; hospitalized patients; predictive model
Mesh:
Year: 2017 PMID: 28508776
Source DB: PubMed Journal: Stud Health Technol Inform ISSN: 0926-9630