The Use of Artificial Intelligence in the Evaluation of Knee Pathology

被引:18
作者
Garwood, Elisabeth R. [1 ,2 ]
Tai, Ryan [1 ,2 ]
Joshi, Ganesh [1 ,2 ]
Watts, George J. [1 ,2 ]
机构
[1] Univ Massachusetts, Mem Med Ctr, Dept Radiol, Div Musculoskeletal Imaging & Intervent, Worcester, MA 01655 USA
[2] Univ Massachusetts, Med Sch, 55 Lake Ave North, Worcester, MA 01655 USA
关键词
artificial intelligence; magnetic resonance imaging; deep learning; knee; ANTERIOR CRUCIATE LIGAMENT; MENISCAL TEARS; OSTEOARTHRITIS; DIAGNOSIS; ARTHRITIS; INJURIES;
D O I
10.1055/s-0039-3400264
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Artificial intelligence (AI) holds the potential to revolutionize the field of radiology by increasing the efficiency and accuracy of both interpretive and noninterpretive tasks. We have only just begun to explore AI applications in the diagnostic evaluation of knee pathology. Experimental algorithms have already been developed that can assess the severity of knee osteoarthritis from radiographs, detect and classify cartilage lesions, meniscal tears, and ligament tears on magnetic resonance imaging, provide automatic quantitative assessment of tendon healing, detect fractures on radiographs, and predict those at highest risk for recurrent bone tumors. This article reviews and summarizes the most current literature.
引用
收藏
页码:21 / 29
页数:9
相关论文
共 50 条
  • [21] Artificial Intelligence and Lung Pathology
    Caranfil, Emanuel
    Lami, Kris
    Uegami, Wataru
    Fukuoka, Junya
    ADVANCES IN ANATOMIC PATHOLOGY, 2024, 31 (05) : 344 - 351
  • [22] Artificial intelligence in diagnostic pathology
    Saba Shafi
    Anil V. Parwani
    Diagnostic Pathology, 18
  • [23] Artificial intelligence in diagnostic pathology
    Shafi, Saba
    Parwani, Anil V.
    DIAGNOSTIC PATHOLOGY, 2023, 18 (01)
  • [24] Explainable artificial intelligence in pathology
    Klauschen, Frederick
    Dippel, Jonas
    Keyl, Philipp
    Jurmeister, Philipp
    Bockmayr, Michael
    Mock, Andreas
    Buchstab, Oliver
    Alber, Maximilian
    Ruff, Lukas
    Montavon, Gregoire
    Mueller, Klaus-Robert
    PATHOLOGIE, 2024, 45 (02): : 133 - 139
  • [25] Artificial intelligence and machine learning in knee arthroplasty ☆
    Rodriguez, Hugo C.
    Rust, Brandon D.
    Roche, Martin W.
    Gupta, Ashim
    KNEE, 2025, 54 : 28 - 49
  • [26] Deep learning in knee imaging: a systematic review utilizing a Checklist for Artificial Intelligence in Medical Imaging (CLAIM)
    Si, Liping
    Zhong, Jingyu
    Huo, Jiayu
    Xuan, Kai
    Zhuang, Zixu
    Hu, Yangfan
    Wang, Qian
    Zhang, Huan
    Yao, Weiwu
    EUROPEAN RADIOLOGY, 2022, 32 (02) : 1353 - 1361
  • [27] Evaluation of Attitudes and Perceptions in Students about the Use of Artificial Intelligence in Dentistry
    Karan-Romero, Milan
    Salazar-Gamarra, Rodrigo Ernesto
    Leon-Rios, Ximena Alejandra
    DENTISTRY JOURNAL, 2023, 11 (05)
  • [28] Use of Artificial Intelligence in Dermatology
    De, Abhishek
    Sarda, Aarti
    Gupta, Sachi
    Das, Sudip
    INDIAN JOURNAL OF DERMATOLOGY, 2020, 65 (05) : 352 - 357
  • [29] Multi-modality artificial intelligence in digital pathology
    Qiao, Yixuan
    Zhao, Lianhe
    Luo, Chunlong
    Luo, Yufan
    Wu, Yang
    Li, Shengtong
    Bu, Dechao
    Zhao, Yi
    BRIEFINGS IN BIOINFORMATICS, 2022, 23 (06)
  • [30] Artificial intelligence as the next step towards precision pathology
    Acs, B.
    Rantalainen, M.
    Hartman, J.
    JOURNAL OF INTERNAL MEDICINE, 2020, 288 (01) : 62 - 81