Machine Learning Consensus Clustering Approach for Hospitalized Patients with Dysmagnesemia

Background: The objectives of this study were to classify patients with serum magnesium derangement on hospital admission into clusters using unsupervised machine learning approach and to evaluate the mortality risks among these distinct clusters. Methods: Consensus cluster analysis was performed ba...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Diagnostics (Basel) Jg. 11; H. 11; S. 2119
Hauptverfasser:	Thongprayoon, Charat, Sy-Go, Janina Paula T., Nissaisorakarn, Voravech, Dumancas, Carissa Y., Keddis, Mira T., Kattah, Andrea G., Pattharanitima, Pattharawin, Vallabhajosyula, Saraschandra, Mao, Michael A., Qureshi, Fawad, Garovic, Vesna D., Dillon, John J., Erickson, Stephen B., Cheungpasitporn, Wisit
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 15.11.2021 MDPI
Schlagworte:	Age Algorithms Artificial intelligence Cardiovascular disease Clinical outcomes Cluster analysis clustering Comorbidity consensus clustering Diabetes dysmagnesemia electrolytes Hospitalization Hospitals Hypertension hypomagnesemia Laboratories Machine learning Mortality Patients Signal transduction Variables United States > US
ISSN:	2075-4418, 2075-4418
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!