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The Role of Machine Learning in LOS Reduction for Patients Affected by Lower Limb Fracture

Conference Paper
Publication Date:
2025
abstract:
The estimation of the Length of Stay (LOS) is a critical factor in clinical and managerial decision-making, helping healthcare professionals optimize hospital efficiency. For patients with orthopedic trauma, particularly those with lower limb fractures, LOS prediction becomes essential for resource planning and improving patient care. This study aims to analyze and predict LOS for patients with lower limb fractures admitted to the A.O.R.N. “Antonio Cardarelli” hospital in Naples. To achieve this, five neural network-based classifiers were implemented, and their performances were compared with those obtained in previous studies conducted by our research group, which employed well-established Artificial Intelligence (AI) models.
Iris type:
4.1 Contributo in Atti di convegno
Keywords:
LOS; Lower Limb Fracture; Machine learning
List of contributors:
Fidecicchi, A.; Santalucia, I.; Toscano, A.; D'Amore, A.; Bernardo, C.; Improta, G.
Handle:
https://iris.unipv.it/handle/11571/1544060
Book title:
Studies in Health Technology and Informatics
Published in:
STUDIES IN HEALTH TECHNOLOGY AND INFORMATICS
Journal
STUDIES IN HEALTH TECHNOLOGY AND INFORMATICS
Series
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