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Analyzing LOS Variation for Patients Under Emergency Interventions: 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

Cholecystectomy and Appendectomy are the most frequent procedures in emergency general surgery. Emergency surgeries represent particularly important procedures in health care as they include various surgical specialties and represent a significant percentage of surgeries sustained in a hospital. This will have a reply is in terms of management of the resources that of costs supported from the hospital. The value of the average hospital stay, LOS, is an important parameter for the proper management of hospitals, providing support to clinicians. This study was conducted with the aim of predicting LOS for all patients undergoing appendectomy and cholecystectomy in the University Hospital “San Giovanni di Dio e Ruggi d’Aragona” of Salerno (Italy) and the A.O.R.N. “Antonio Cardarelli” of Naples (Italy).

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Author information

Authors and Affiliations

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

    Alfonso Maria Ponsiglione

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

    Marta Rosaria Marino, Francesco Smeraglia, Enrico Festa & Arianna Scala

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

    Eliana Raiola & Giuseppe Russo

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

    Anna Borrelli

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  1. Alfonso Maria Ponsiglione
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  2. Marta Rosaria Marino
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  3. Eliana Raiola
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  4. Francesco Smeraglia
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  7. Anna Borrelli
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  8. Arianna Scala
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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). Analyzing LOS Variation for Patients Under Emergency Interventions: 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_42

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