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2023 | OriginalPaper | Buchkapitel

Predictive Algorithms to Study the Hospitalization for Knee Replacement Surgery: A Bicentric Study

verfasst von : Alfonso Maria Ponsiglione, Marta Rosaria Marino, Eliana Raiola, Giuseppe Russo, Giovanni Balato, Enrico Festa, Giovanni Rossi, Anna Borrelli, Maria Triassi, Maria Romano

Erschienen in: Biomedical and Computational Biology

Verlag: Springer International Publishing

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Abstract

Knee replacement surgery is one of the most interesting procedures in surgery. Patients generally have an LOS of about 5 days and when it increases it is related to clinical factors and the patient’s comorbidity. Duration of stay (LOS) is a useful tool for monitoring patients and useful for hospital administrators to assess the efficiency of the hospital. This study was conducted with the aim of analyzing LOS for all patients who underwent a procedure for the insertion or review of knee prostheses at the University Hospital “San Giovanni di Dio e Ruggi d’Aragona” in Salerno (Italy) and the A.O.R.N. “Antonio Cardarelli” in Naples (Italy). The goal of the work was to make a comparison between the two hospitals. The analysis was conducted with Multiple Linear Regression analysis and the implementation of Machine Learning algorithms: Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM) and Gradient Boosted Trees (GBT).

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Titel: Predictive Algorithms to Study the Hospitalization for Knee Replacement Surgery: A Bicentric Study
verfasst von: Alfonso Maria Ponsiglione
Marta Rosaria Marino
Eliana Raiola
Giuseppe Russo
Giovanni Balato
Enrico Festa
Giovanni Rossi
Anna Borrelli
Maria Triassi
Maria Romano
Verlag: Springer International Publishing
Buch: Biomedical and Computational Biology
Print ISBN: 978-3-031-25190-0

Electronic ISBN: 978-3-031-25191-7

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-3-031-25191-7_49

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