首页|Application and Prospects of Deep Learning Technology in Fracture Diagnosis

Application and Prospects of Deep Learning Technology in Fracture Diagnosis

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Artificial intelligence(AI)is an interdisciplinary field that combines computer technology,mathematics,and several other fields.Recently,with the rapid development of machine learning(ML)and deep learning(DL),significant progress has been made in the field of AI.As one of the fastest-growing branches,DL can effectively extract features from big data and optimize the performance of various tasks.Moreover,with advancements in digital imaging technology,DL has become a key tool for processing high-dimensional medical image data and conducting medical image analysis in clinical applications.With the development of this technology,the diagnosis of orthopedic diseases has undergone significant changes.In this review,we describe recent research progress on DL in fracture diagnosis and discuss the value of DL in this field,providing a reference for better integration and development of DL technology in orthopedics.

deep learningartificial intelligencefracturediagnosismedical image analysisorthopedics

Jia-yao ZHANG、Jia-ming YANG、Xin-meng Wang、Hong-lin WANG、Hong ZHOU、Zi-neng YAN、Yi XIE、Peng-ran LIU、Zhi-wei HAO、Zhe-wei YE

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Department of Orthopedics,Fuzhou University Affiliated Provincial Hospital,Fuzhou 350013,China

Department of Orthopedics,Fujian Provincial Hospital,Fuzhou 350013,China

Intelligent Medical Laboratory,Union Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430022,China

Department of Orthopedics,Union Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430022,China

Department of Biochemistry and Molecular Biology,School of Basic Medical Sciences,Dali University,Dali 671000,China

School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074,China

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2024

10.1007/s11596-024-2928-5

当代医学科学(英文)
华中科技大学同济医学院

当代医学科学(英文)

影响因子：0.748
ISSN：2096-5230
年,卷(期)：2024.44(6)