Artificial intelligence reshapes current understanding and management of osteoarthritis: A narrative review

Current practice of osteoarthritis has its insufficiencies which researchers are tackling with artificial intelligence (AI). This article discusses three kinds of AI models, namely diagnostic models, prediction models and morphological models. Diagnostic models enhance efficiency in diagnosis by providing an automated algorithm in knee images processing. Prediction models utilize behavioral and radiological data to assess the risk of osteoarthritis before symptom onset and needs to perform surgery. Morphological models detect biomechanical changes to facilitate understanding of pathophysiology and provide personalized intervention. Through reviewing present evidence, we demonstrate that AI could assist doctors in diagnosis, predict osteoarthritis and guide future research.

Automated summary

AI can provide assistance in the field of osteoarthritis. Diagnostic models can improve diagnostic efficiency, prediction models can assess the risk of osteoarthritis, and morphological models can detect biomechanical changes. Through reviewing present evidence, it is demonstrated that AI can assist doctors in diagnosis and prediction, and guide future research.