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人工智能在肌肉骨骼疾病患者诊断与预后评估中的应用

Artificial Intelligence in the Diagnosis and Prognostication of the Musculoskeletal Patient.

作者信息

Girod Miguel M, Saniei Sami, Ulrich Marisa N, Bukowiec Lainey G, Mulford Kellen L, Taunton Michael J, Wyles Cody C

机构信息

Orthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.

Mayo Clinic Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.

出版信息

HSS J. 2025 May 28:15563316251339660. doi: 10.1177/15563316251339660.


DOI:10.1177/15563316251339660
PMID:40454292
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12119539/
Abstract

As artificial intelligence (AI) advances in healthcare, encompassing robust applications for the diagnosis and prognostication of musculoskeletal diseases, clinicians must increasingly understand the implications of machine learning and deep learning in their practice. This review article explores computer vision algorithms and patient-specific, multimodal prediction models; provides a simple framework to guide discussion on the limitations of AI model development; and introduces the field of generative AI.

摘要

随着人工智能(AI)在医疗保健领域的发展,涵盖了用于肌肉骨骼疾病诊断和预后的强大应用,临床医生必须越来越了解机器学习和深度学习在其实践中的影响。这篇综述文章探讨了计算机视觉算法和针对特定患者的多模态预测模型;提供了一个简单的框架来指导关于AI模型开发局限性的讨论;并介绍了生成式AI领域。

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本文引用的文献

[1]
Characterizing hip joint morphology using a multitask deep learning model.

J Hip Preserv Surg. 2024-12-12

[2]
A Deep Learning Tool for Minimum Joint Space Width Calculation on Antero-posterior Knee Radiographs.

J Arthroplasty. 2025-8

[3]
TKA-AID: An Uncertainty-Aware Deep Learning Classifier to Identify Total Knee Arthroplasty Implants.

J Arthroplasty. 2025-8

[4]
Exploring prospects, hurdles, and road ahead for generative artificial intelligence in orthopedic education and training.

BMC Med Educ. 2024-12-28

[5]
Leveraging AI models for lesion detection in osteonecrosis of the femoral head and T1-weighted MRI generation from radiographs.

J Orthop Res. 2025-3

[6]
Uncertainty-Aware Deep Learning Characterization of Knee Radiographs for Large-Scale Registry Creation.

J Arthroplasty. 2025-5

[7]
Analyzing Racial Differences in Imaging Joint Replacement Registries Using Generative Artificial Intelligence: Advancing Orthopaedic Data Equity.

Arthroplast Today. 2024-9-23

[8]
Development and benchmarking of a Deep Learning-based MRI-guided gross tumor segmentation algorithm for Radiomics analyses in extremity soft tissue sarcomas.

Radiother Oncol. 2024-8

[9]
Generative models improve fairness of medical classifiers under distribution shifts.

Nat Med. 2024-4

[10]
MRI-based synthetic CT for assessment of the bony elements of the sacroiliac joints in children.

Insights Imaging. 2024-2-18

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