Year: 2025
Type: article
Abstract: This article intends to explore the development prospect of Artificial Intelligence (AI) application in sports injury prediction. This field is not only important for sports industry but also for medical fields since the results of injury prediction could be an instruction for medical care. Specifically, the article states some AI techniques to make predictions. The article will elaborate on these techniques. The article states steps for data cleaning which are a vital step for AI models. In addition, the article lists machine learning models including random forests, Support Vector Machines, K-Nearest Neighbors and deep learning models including Convolutional Neural Networks, Artificial Neural Networks, Recurrent Neural Networks. The article would focus on the principles of these models. According to principles, models are really useful and promising for personalized injury prediction since AI models can analyze complex patterns of variables. Some models like Recurrent Neural Networks that require sequential data can get accurate relationships between data and time and make better prediction.
Author: Qifan Huo
Language: English
Subfield: Orthopedics and Sports Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4415166150
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