{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T19:04:48Z","timestamp":1792177488010,"version":"4.4.0"},"reference-count":72,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,4,14]],"date-time":"2022-04-14T00:00:00Z","timestamp":1649894400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Fractures of the femur are a frequent problem in elderly people, and it has been demonstrated that treating them with a diagnostic\u2013therapeutic\u2013assistance path within 48 h of admission to the hospital reduces complications and shortens the length of the hospital stay (LOS). In this paper, the preoperative data of 1082 patients were used to further extend the previous research and to generate several models that are capable of predicting the overall LOS: First, the LOS, measured in days, was predicted through a regression analysis; then, it was grouped by weeks and was predicted with a classification analysis. The KNIME analytics platform was applied to divide the dataset for a hold-out cross-validation, perform a multiple linear regression and implement machine learning algorithms. The best coefficient of determination (R2) was achieved by the support vector machine (R2 = 0.617), while the mean absolute error was similar for all the algorithms, ranging between 2.00 and 2.11 days. With regard to the classification analysis, all the algorithms surpassed 80% accuracy, and the most accurate algorithm was the radial basis function network, at 83.5%. The use of these techniques could be a valuable support tool for doctors to better manage orthopaedic departments and all their resources, which would reduce both waste and costs in the context of healthcare.<\/jats:p>","DOI":"10.3390\/bioengineering9040172","type":"journal-article","created":{"date-parts":[[2022,4,14]],"date-time":"2022-04-14T21:44:06Z","timestamp":1649972646000},"page":"172","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Machine Learning and Regression Analysis to Model the Length of Hospital Stay in Patients with Femur Fracture"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7290-6432","authenticated-orcid":false,"given":"Carlo","family":"Ricciardi","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples \u201cFederico II\u201d, 80125 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1346-515X","authenticated-orcid":false,"given":"Alfonso Maria","family":"Ponsiglione","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples \u201cFederico II\u201d, 80125 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9735-5227","authenticated-orcid":false,"given":"Arianna","family":"Scala","sequence":"additional","affiliation":[{"name":"Department of Public Health, University Hospital of Naples \u201cFederico II\u201d, 80131 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2633-8507","authenticated-orcid":false,"given":"Anna","family":"Borrelli","sequence":"additional","affiliation":[{"name":"Health Department, University Hospital of Salerno \u201cSan Giovanni di Dio e Ruggi d\u2032Aragona\u201d, 84126 Salerno, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mario","family":"Misasi","sequence":"additional","affiliation":[{"name":"Department of the Orthopaedics, National Hospital (A.O.R.N.) Antonio Cardarelli, 80131 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gaetano","family":"Romano","sequence":"additional","affiliation":[{"name":"Department of the Orthopaedics, National Hospital (A.O.R.N.) Antonio Cardarelli, 80131 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giuseppe","family":"Russo","sequence":"additional","affiliation":[{"name":"National Hospital (A.O.R.N.) Antonio Cardarelli, 80131 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria","family":"Triassi","sequence":"additional","affiliation":[{"name":"Department of Public Health, University Hospital of Naples \u201cFederico II\u201d, 80131 Naples, Italy"},{"name":"Interdepartmental Center for Research in Healthcare, Management and Innovation in Healthcare (CIRMIS), University of Study of Naples \u201cFederico II\u201d, 80131 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9485-1687","authenticated-orcid":false,"given":"Giovanni","family":"Improta","sequence":"additional","affiliation":[{"name":"Department of Public Health, University Hospital of Naples \u201cFederico II\u201d, 80131 Naples, Italy"},{"name":"Interdepartmental Center for Research in Healthcare, Management and Innovation in Healthcare (CIRMIS), University of Study of Naples \u201cFederico II\u201d, 80131 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,14]]},"reference":[{"key":"ref_1","first-page":"97","article-title":"Incidence and Socioeconomic Burden of Hip Fractures in Italy","volume":"57","author":"Rossini","year":"2005","journal-title":"Reumatismo"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2907","DOI":"10.1007\/s00264-018-3881-3","article-title":"Lateral Locked Plating for Distal Femur Fractures by Low-Energy Trauma: What Makes a Difference in Healing?","volume":"42","author":"Kim","year":"2018","journal-title":"Int. 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