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

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Biomedical and Computational Biology (BECB 2022)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 13637))

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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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Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Information Technology, University of Study of Naples “Federico II”, Naples, Italy

    Alfonso Maria Ponsiglione & Maria Romano

  2. Department of Public Health, University of Naples “Federico II”, Naples, Italy

    Marta Rosaria Marino, Giovanni Balato, Enrico Festa & Maria Triassi

  3. A.O.R.N. “A. Cardarelli”, Naples, Italy

    Eliana Raiola & Giuseppe Russo

  4. San Giovanni di Dio e Ruggi d’Aragona” University Hospital, Salerno, Italy

    Giovanni Rossi & Anna Borrelli

  5. Interdepartmental Center for Research in Healthcare Management and Innovation in Healthcare (CIRMIS), University of Naples “Federico II”, Naples, Italy

    Maria Triassi

Authors
  1. Alfonso Maria Ponsiglione
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  2. Marta Rosaria Marino
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  3. Eliana Raiola
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  4. Giuseppe Russo
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  5. Giovanni Balato
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  6. Enrico Festa
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  7. Giovanni Rossi
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  9. Maria Triassi
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  10. Maria Romano
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Corresponding author

Correspondence to Marta Rosaria Marino .

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Editors and Affiliations

  1. University of Technology Sydney, Sydney, NSW, Australia

    Shiping Wen

  2. Nanchang Hangkong University, Nanchang, China

    Cihui Yang

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Ponsiglione, A.M. et al. (2023). Predictive Algorithms to Study the Hospitalization for Knee Replacement Surgery: A Bicentric Study. In: Wen, S., Yang, C. (eds) Biomedical and Computational Biology. BECB 2022. Lecture Notes in Computer Science(), vol 13637. Springer, Cham. https://doi.org/10.1007/978-3-031-25191-7_49

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  • DOI: https://doi.org/10.1007/978-3-031-25191-7_49

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