Novel Study for the Early Identification of Injury Risks in Athletes Using Machine Learning Techniques

Novel Study for the Early Identification of Injury Risks in Athletes Using Machine Learning Techniques

This innovative study addresses the prevalent issue of sports injuries, particularly focusing on ankle injuries, utilizing advanced analytical tools such as artificial intelligence (AI) and machine learning (ML). Employing a logistic regression model, the research achieves a remarkable accuracy of 9...

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Bibliographic Details
Main Authors: Rocío Elizabeth Duarte Ayala, David Pérez Granados, Carlos Alberto González Gutiérrez, Mauricio Alberto Ortega Ruíz, Natalia Rojas Espinosa, Emanuel Canto Heredia
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Applied Sciences
Subjects:
injury prediction
athlete health
machine learning
sports risk factors
preventive strategies
kinesiophobia
Online Access:https://www.mdpi.com/2076-3417/14/2/570

Internet

https://www.mdpi.com/2076-3417/14/2/570

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