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Application progress of machine learning in diagnosis and treatment of the coronavirus disease 2019
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Hua Guo1, 2, Jun-Yu Ding1, 2, Chang-Xin Liu1, 2, Kan Zhang2, Lin Ma2, Bo Wang1, 2, Hui-Jun Zhao1, 2, Man-Ya Song1, 2, Xi-Zhou Guan2, *
Medical Journal of Chinese People’s Liberation Army | 2023, 48(7) : 863 - 870
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Medical Journal of Chinese People’s Liberation Army | 2023, 48(7): 863-870
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Application progress of machine learning in diagnosis and treatment of the coronavirus disease 2019
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Hua Guo1, 2, Jun-Yu Ding1, 2, Chang-Xin Liu1, 2, Kan Zhang2, Lin Ma2, Bo Wang1, 2, Hui-Jun Zhao1, 2, Man-Ya Song1, 2, Xi-Zhou Guan2, *
Affiliations
  • 1Medical School of Chinese PLA, Beijing 100853, China
  • 2Department of Respiratory and Critical Care Medicine, the Eighth Medical Center of Chinese PLA General Hospital, Beijing 100091, China
Published: 2023-07-28 doi: 10.11855/j.issn.0577-7402.3029.2022.1214
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Since the outbreak of the coronavirus disease 2019 (COVID-19), machine learning has been widely used in forecasting the epidemic trend of COVID-19, screening and tracking high-risk people, early diagnosis and monitoring of patients, etc., which has greatly improved the efficiency of information processing during the epidemic period and provided efficient decision support for clinicians. However, due to the different data types and scales and training methods used to develop models, machine learning that perform diagnosis or prognosis tasks also have different limitations. This review introduces the application of machine learning in the diagnosis and prognosis of COVID-19 from the aspects of machine learning combined with imaging data, laboratory results, and the model trained by integrating these two aspects, trying to provide more practical ways for machine learning in training and application.

coronavirus disease 2019  /  diagnosis  /  prognosis  /  machine learning
Hua Guo, Jun-Yu Ding, Chang-Xin Liu, Kan Zhang, Lin Ma, Bo Wang, Hui-Jun Zhao, Man-Ya Song, Xi-Zhou Guan. Application progress of machine learning in diagnosis and treatment of the coronavirus disease 2019[J]. Medical Journal of Chinese People’s Liberation Army, 2023 , 48 (7) : 863 -870 . DOI: 10.11855/j.issn.0577-7402.3029.2022.1214
Year 2023 volume 48 Issue 7
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Article Info
doi: 10.11855/j.issn.0577-7402.3029.2022.1214
  • Receive Date:2021-12-21
  • Online Date:2025-12-03
  • Published:2023-07-28
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  • Received:2021-12-21
  • Accepted:2022-08-12
Affiliations
    1Medical School of Chinese PLA, Beijing 100853, China
    2Department of Respiratory and Critical Care Medicine, the Eighth Medical Center of Chinese PLA General Hospital, Beijing 100091, China

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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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种数
Number of
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占总种数比例
Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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