Deep Learning-Adjusted Monitoring of In-Hospital Mortality after Liver Transplantation

: Surgeries represent a mainstay of medical care globally. Patterns of complications are frequently recognized late and place a considerable burden on health care systems. The aim was to develop and test the first deep learning-adjusted CUSUM program (DL-CUSUM) to predict and monitor in-hospital mor...

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Veröffentlicht in:	Journal of clinical medicine 2024-10, Vol.13 (20), p.6046
Hauptverfasser:	Börner, Nikolaus, Schoenberg, Markus B, Pöllmann, Benedikt, Pöschke, Philipp, Böhm, Christian, Koch, Dominik, Drefs, Moritz, Koliogiannis, Dionysios, Andrassy, Joachim, Werner, Jens, Guba, Markus Otto
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Body mass index Datasets Deep learning Health aspects Hospital care Hospitals Ischemia Liver Liver transplants Machine learning Medical prognosis Methods Missing data Mortality Neural networks Open source software Patient monitoring Patient outcomes Prevention Process controls Review boards Technology application Transplantation Variables
Online-Zugang:	Volltext
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