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综   述||Reviews                       磁共振成像  2024年7月第15卷第7期  Chin J Magn Reson Imaging, Jul, 2024, Vol. 15, No. 7


           目前在头颈部动脉粥样斑块上的研究以影像组学为                              [10] YAN  J, WANG  X  F.  Unsupervised  and  semi-supervised  learning:  the
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           主,DL 应用相对较少,两者内部运作机制不可见以                                2022, 111(6): 1527-1538. DOI: 10.1111/tpj.15905.
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           及大量高维特征与病灶具体临床特征的相关性等问                                  classification  of  real-time  tissue  elastography  for  hepatic  fibrosis  in
           题,在临床应用转化上存在一定问题                  [50-51] 。其次,由         patients with chronic hepatitis B[J/OL]. Comput Biol Med, 2017, 89:
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           证。最后多数研究使用单一的 ML 模型或 DL 算法,                         [13] MATTEUCCI G, PIASINI E, ZOCCOLAN D. Unsupervised learning
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           可视化或与医学知识图谱相结合推动 AI 的临床转                                23(5): bbac120 [2024-02-27]. https://pubmed.ncbi.nlm.nih.gov/35514190/.
           化,建立跨设备、跨平台的标准化扫描和数据采集流                                 DOI: 10.1093/bib/bbac120.
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           程,确保模型的可重复性和泛化能力,多中心合作或                                 angiography[J/OL]. Atherosclerosis, 2023, 366: 40-41 [2024-02-27]. https://
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           建立头颈动脉粥样硬化疾病数据库尽量加强模型的                                  01.006.
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           泛化能力,以及与基因组学和生物标志物的结合,将                                 learning for screening, diagnosis, and detection of glaucoma progression
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           而为患者提供个性化治疗方案,提高其生活质量。                              [17] WAGNER M W, NAMDAR K, BISWAS A, et al. Radiomics, machine
                                                                   learning,  and  artificial  intelligence-what  the  neuroradiologist  needs  to
               作者利益冲突声明:全体作者均声明无利益冲突。                              know[J]. Neuroradiology, 2021, 63(12): 1957-1967. DOI: 10.1007/s00234-
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               作者贡献声明:曾献军拟定本综述的写作思路,                           [18] MCBEE  M  P, AWAN  O A,  COLUCCI A  T,  et  al.  Deep  learning  in
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                                                                   based  on  CNN  and  sliding  window  LSTM  for  spike  sorting[J/OL].
           综述的参考文献;欧阳烽、吕联江、徐紫荷获取、分析                                Comput Biol Med, 2023, 159: 106879 [2024-02-27]. https://pubmed.ncbi.
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           意对本研究的所有方面负责,确保本研究的准确性                                  3084827.
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