Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz

Logo MUG-Forschungsportal

Gewählte Publikation:

SHR Neuro Krebs Kardio Lipid Stoffw Microb

Veeranki, SPK; Hayn, D; Jauk, S; Quehenberger, F; Kramer, D; Leodolter, W; Schreier, G.
An Improvised Classification Model for Predicting Delirium.
Stud Health Technol Inform. 2019; 264: 1566-1567. Doi: 10.3233/SHTI190537
PubMed FullText FullText_MUG

 

Co-Autor*innen der Med Uni Graz
Jauk Stefanie
Quehenberger Franz
Altmetrics:

Dimensions Citations:

Plum Analytics:

Scite (citation analytics):

Abstract:
With the vast increase of digital healthcare data, there is an opportunity to mine the data for understanding inherent health patterns. Although machine-learning techniques demonstrated their applications in healthcare to answer several questions, there is still room for improvement in every aspect. In this paper, we are demonstrating a method that improves the performance of a delirium prediction model using random forest in combination with logistic regression.
Find related publications in this database (using NLM MeSH Indexing)
Delirium -
Humans -
Logistic Models -
Machine Learning -

© Med Uni Graz Impressum