Eigner I, Bodendorf F (2018)
Publication Language: English
Publication Type: Journal article, Online publication
Publication year: 2018
Book Volume: 60
Pages Range: 195–205
Article Number: 2196-7032
Journal Issue: 4
Readmission prediction in hospitals is a highly complex task involving multiple risk factors that can vary among different disease groups. We address this issue by implementing multiple cross-validated classification models within an intelligent CDSS to enhance patient discharge management. Depending on the diagnosis, the system selects and applies the appropriate model and visualises the prediction results. In addition, the cost and reimbursement development for each episode are determined. The architecture of the CDSS and the integration of the prediction models are presented in this paper.
APA:
Eigner, I., & Bodendorf, F. (2018). An intelligent decision support system for readmission prediction in healthcare. it - Information Technology, 60(4), 195–205. https://doi.org/10.1515/itit-2018-0003
MLA:
Eigner, Isabella, and Freimut Bodendorf. "An intelligent decision support system for readmission prediction in healthcare." it - Information Technology 60.4 (2018): 195–205.
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