Medizinische Universität Graz - Research portal
Selected Publication:
SHR Neuro Cancer Cardio Lipid Metab 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
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- Co-authors Med Uni Graz
- Jauk Stefanie
- Quehenberger Franz
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- 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 -