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- W4382632146 abstract "The revolutions of recent years in health care have involved several areas ranging from patient treatment to resource management. Therefore, several strategies have been put in place to increase patient value while trying to reduce spending. Several indicators have arisen to evaluate the performance of healthcare processes. The main one is Length of Stay (LOS). In this study, classification algorithms were used to predict the LOS of patients undergoing lower extremity surgery, an increasingly common condition given the progressive aging of the population. The context is the Evangelical Hospital Betania in Naples (Italy) in 2019-2020, which augments a multicenter study conducted by the same research team on several hospitals in southern Italy. All selected algorithms show an Accuracy above 90% but among them, the best is Logistic Regression with a value reaching 94%." @default.
- W4382632146 created "2023-07-01" @default.
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- W4382632146 date "2023-06-29" @default.
- W4382632146 modified "2023-09-27" @default.
- W4382632146 title "The Classification Algorithms Applied to the Inpatient Stay for Lower Limb Surgery" @default.
- W4382632146 doi "https://doi.org/10.3233/shti230442" @default.
- W4382632146 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37386976" @default.
- W4382632146 hasPublicationYear "2023" @default.
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