人工智能重塑当前对骨关节炎的理解和管理:叙述性回顾

Hin Ting Victor Yick, P. Chan, Chunyi Wen, W. C. Fung, C. Yan, K. Chiu
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引用次数: 0

摘要

目前骨关节炎的治疗存在不足,研究人员正在用人工智能(AI)来解决这些问题。本文讨论了三种人工智能模型,即诊断模型、预测模型和形态模型。诊断模型通过提供膝关节图像处理的自动算法来提高诊断效率。预测模型利用行为和放射学数据在症状出现和需要进行手术之前评估骨关节炎的风险。形态学模型检测生物力学变化,以促进病理生理学的理解和提供个性化的干预。通过回顾现有的证据,我们证明人工智能可以帮助医生诊断、预测骨关节炎并指导未来的研究。
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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.
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CiteScore
0.60
自引率
0.00%
发文量
36
审稿时长
8 weeks
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