Artificial Intelligence and Machine Learning in Sport Medicines
Keywords:
Orthopedic surgery; Machine learning; Supervised learning; Unsupervised machine learning; Neuralnetwork.
Abstract
Orthopedic sports medicine is starting to feel the impact of machine learning (ML), which is transforming healthcare procedures. Orthopedic sports medicine professionals can now analyze enormous volumes of patient data to obtain insights that were previously unreachable through traditional approaches by utilizing machine learning algorithms .Large datasets can be tested more easily with machine learning to find complex saga between input and output variables. These correlations may be more complicated than what can be achieved with conventional statistical techniques, allowing for precise output predictions. For healthcare data, supervised learning is the most popular machine learning technique. Supervised learning algorithms have been applied in recent research to forecast individual patient outcomes after surgery, such as hip arthroscopy. These algorithms have the ability to improve postoperative care, optimize surgical procedures, and improve preoperative planning by utilizing extent volumes of patient data, which will ultimately improve patient outcomes in orthopedic surgery.
Published
2024-03-25
Section
Research Article
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