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Machine Learning Applications in Orthopaedic Imaging.机器学习在骨科成像中的应用。
J Am Acad Orthop Surg. 2020 May 15;28(10):e415-e417. doi: 10.5435/JAAOS-D-19-00688.
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Machine Learning and Deep Learning in Medical Imaging: Intelligent Imaging.医学成像中的机器学习与深度学习：智能成像
J Med Imaging Radiat Sci. 2019 Dec;50(4):477-487. doi: 10.1016/j.jmir.2019.09.005. Epub 2019 Oct 7.
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Basic Artificial Intelligence Techniques: Machine Learning and Deep Learning.基础人工智能技术：机器学习和深度学习。
Radiol Clin North Am. 2021 Nov;59(6):933-940. doi: 10.1016/j.rcl.2021.06.004.
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Artificial Intelligence in Nuclear Cardiology.核心脏病学中的人工智能
J Nucl Med. 2019 Aug;60(8):1042-1043. doi: 10.2967/jnumed.118.222356. Epub 2019 Mar 29.
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Artificial intelligence in medical imaging of the liver.人工智能在肝脏医学影像中的应用。
World J Gastroenterol. 2019 Feb 14;25(6):672-682. doi: 10.3748/wjg.v25.i6.672.
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Artificial intelligence in orthopedics: three strategies for deep learning with orthopedic specific imaging.骨科中的人工智能：针对骨科特定成像的深度学习的三种策略。
Knee Surg Sports Traumatol Arthrosc. 2022 Mar;30(3):758-761. doi: 10.1007/s00167-021-06838-8. Epub 2022 Jan 13.
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Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?人工智能、机器学习、深度学习和认知计算：这些术语是什么意思，它们将如何影响医疗保健？
J Arthroplasty. 2018 Aug;33(8):2358-2361. doi: 10.1016/j.arth.2018.02.067. Epub 2018 Feb 27.
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Artificial intelligence in medical imaging.医学影像中的人工智能。
Magn Reson Imaging. 2020 May;68:A1-A4. doi: 10.1016/j.mri.2019.12.006. Epub 2019 Dec 16.
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Artificial intelligence, machine learning, and deep learning in orthopedic surgery.骨科手术中的人工智能、机器学习和深度学习
Jt Dis Relat Surg. 2022;33(2):484-485. doi: 10.52312/jdrs.2022.57906.
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Artificial Intelligence in Spine Care.人工智能在脊柱护理中的应用。
Clin Spine Surg. 2021 May 1;34(4):121-124. doi: 10.1097/BSD.0000000000001082.
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Deep learning-assisted detection of meniscus and anterior cruciate ligament combined tears in adult knee magnetic resonance imaging: a crossover study with arthroscopy correlation.深度学习辅助检测成人膝关节磁共振成像中的半月板和前交叉韧带联合撕裂：一项与关节镜检查相关性的交叉研究
Int Orthop. 2025 Apr 28. doi: 10.1007/s00264-025-06531-2.
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Using Google web search to analyze and evaluate the application of ChatGPT in femoroacetabular impingement syndrome.利用谷歌网页搜索分析和评估 ChatGPT 在股骨髋臼撞击综合征中的应用。
Front Public Health. 2024 May 31;12:1412063. doi: 10.3389/fpubh.2024.1412063. eCollection 2024.
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Artificial intelligence-based applications in shoulder surgery leaves much to be desired: a systematic review.基于人工智能的肩部手术应用仍有很大的改进空间：一项系统评价。
JSES Rev Rep Tech. 2023 Jan 7;3(2):189-200. doi: 10.1016/j.xrrt.2022.12.006. eCollection 2023 May.
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A novel application of neural networks to identify potentially effective combinations of biologic factors for enhancement of bone fusion/repair.神经网络在识别生物因素的潜在有效组合以增强骨融合/修复中的新应用。
PLoS One. 2022 Nov 1;17(11):e0276562. doi: 10.1371/journal.pone.0276562. eCollection 2022.
本文引用的文献
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Deep Learning-Based Femoral Cartilage Automatic Segmentation in Ultrasound Imaging for Guidance in Robotic Knee Arthroscopy.基于深度学习的膝关节镜机器人导航中超声成像的股骨软骨自动分割。
Ultrasound Med Biol. 2020 Feb;46(2):422-435. doi: 10.1016/j.ultrasmedbio.2019.10.015. Epub 2019 Nov 22.
2
Potential Liability for Physicians Using Artificial Intelligence.医生使用人工智能的潜在责任。
JAMA. 2019 Nov 12;322(18):1765-1766. doi: 10.1001/jama.2019.15064.
3
Development of an unsupervised machine learning algorithm for the prognostication of walking ability in spinal cord injury patients.开发一种用于预测脊髓损伤患者行走能力的无监督机器学习算法。
Spine J. 2020 Feb;20(2):213-224. doi: 10.1016/j.spinee.2019.09.007. Epub 2019 Sep 13.
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Hip Fracture Discrimination Based on Statistical Multi-parametric Modeling (SMPM).基于统计多参数建模的髋部骨折鉴别。
Ann Biomed Eng. 2019 Nov;47(11):2199-2212. doi: 10.1007/s10439-019-02298-x. Epub 2019 May 31.
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Muscle Type and Gender Recognition Utilising High-Level Textural Representation in Musculoskeletal Ultrasonography.利用肌肉骨骼超声中的高级纹理特征进行肌肉类型和性别识别。
Ultrasound Med Biol. 2019 Jul;45(7):1562-1573. doi: 10.1016/j.ultrasmedbio.2019.02.011. Epub 2019 Apr 13.
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Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet.深度学习辅助膝关节磁共振成像诊断：MRNet 的开发和回顾性验证。
PLoS Med. 2018 Nov 27;15(11):e1002699. doi: 10.1371/journal.pmed.1002699. eCollection 2018 Nov.
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Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine.医学成像中的人工智能：威胁还是机遇？放射科医生再次站在医学创新的前沿。
Eur Radiol Exp. 2018 Oct 24;2(1):35. doi: 10.1186/s41747-018-0061-6.
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Machine learning techniques for medical diagnosis of diabetes using iris images.基于虹膜图像的糖尿病医学诊断的机器学习技术。
Comput Methods Programs Biomed. 2018 Apr;157:121-128. doi: 10.1016/j.cmpb.2018.01.004. Epub 2018 Jan 11.
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High-Risk Breast Lesions: A Machine Learning Model to Predict Pathologic Upgrade and Reduce Unnecessary Surgical Excision.高危乳腺病变：一种预测病理升级和减少不必要手术切除的机器学习模型。
Radiology. 2018 Mar;286(3):810-818. doi: 10.1148/radiol.2017170549. Epub 2017 Oct 17.
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A survey on deep learning in medical image analysis.深度学习在医学图像分析中的应用研究综述。
Med Image Anal. 2017 Dec;42:60-88. doi: 10.1016/j.media.2017.07.005. Epub 2017 Jul 26.
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