| Literature DB >> 32763775 |
Lucas Bulgarelli1, Rodrigo Octávio Deliberato2, Alistair E W Johnson3.
Abstract
Accurate outcome prediction in Intensive Care Units (ICUs) would allow for better treatment planning, risk adjustment of study populations, and overall improvements in patient care. In the past, prognostic models have focused on mortality using simple ordinal severity of illness scores which could be tabulated manually by a human. With the improvements in computing power and proliferation of electronic medical records, entirely new approaches have become possible. Here we review the latest advances in outcome prediction, paying close attention to methods which are widely applicable and provide a high-level overview of the challenges the field currently faces.Entities:
Keywords: Critical Care; Machine learning; Outcome prediction
Mesh:
Year: 2020 PMID: 32763775 DOI: 10.1016/j.jcrc.2020.07.017
Source DB: PubMed Journal: J Crit Care ISSN: 0883-9441 Impact factor: 3.425