[1] |
BAI Shaowen, ZHOU Jihua, DONG Yi, ZHANG Jianfeng, SHI Liang, YANG Kun.
Construction of a visual intelligent identification model for Oncomelania hupensis robertsoni in Yunnan Province based on the EfficientNet⁃B4 model
[J]. Chinese Journal of Schistosomiasis Control, 2024, 36(6): 555-561.
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[2] |
GAO Fenghua.
Prediction of areas of Oncomelania hupensis snail spread in Anhui Province based on five machine learning models
[J]. Chinese Journal of Schistosomiasis Control, 2024, 36(6): 572-576.
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[3] |
ZHU Huiyin, LI Yuting, ZHU Daiqian, WANG Yaqian, ZHANG Jinhong, CHEN Shaoxuan, MA Xiaoyuan, WANG Huidi, LI Hongjun, LI Jian.
Establishment and application of an artificial intelligence⁃assisted platform for detection of parasite eggs
[J]. Chinese Journal of Schistosomiasis Control, 2024, 36(6): 643-648.
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[4] |
ZHOU Yu, TONG Yixin, ZHOU Yibiao.
Application of machine learning models in schistosomiasis control: a review
[J]. Chinese Journal of Schistosomiasis Control, 2024, 36(5): 535-541.
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[5] |
YAN Shuning, YANG Shuo, YANG Hanyin, XIN Yi, XU Bin, HU Wei, LU Yan, ZHENG Bin.
Application of the CRISPR/Cas system in gene editing and nucleic acid detection of parasitic diseases: a review
[J]. Chinese Journal of Schistosomiasis Control, 2024, 36(3): 314-320.
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[6] |
ZHANG Xi, LONG Shaorong, LIU Ruodan, JIANG Peng, CUI Jing, WANG Zhongquan.
Thinking on ideological and political education in Medical Parasitology teaching
[J]. Chinese Journal of Schistosomiasis Control, 2024, 36(1): 87-90.
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[7] |
ZHANG Yuying, CAO Yuanyuan, YANG Kai, WANG Weiming, YANG Mengmeng, CHAI Liying, GU Jiyue, LI Mengyue, LU Yan, ZHOU Huayun, ZHU Guoding, CAO Jun, LU Guangyu.
Risk predictive models of healthcare⁃seeking delay among imported malaria patients in Jiangsu Province based on the machine learning
[J]. Chinese Journal of Schistosomiasis Control, 2023, 35(3): 225-235,243.
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[8] |
ZENG Ting, JIA Tiewu.
Progress in methodology of the Global Burden of Disease Study and its impact on the disease burden of parasitic diseases
[J]. Chinese Journal of Schistosomiasis Control, 2023, 35(3): 299-306.
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[9] |
ZHENG Ruiying, LIU Genyan.
Application of machine learning in clinical predictive models for infectious diseases: a review
[J]. Chinese Journal of Schistosomiasis Control, 2023, 35(3): 317-321.
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[10] |
CHEN Xiaojun, ZHOU Sha, QIU Jingfan, CHEN Lin, XU Zhipeng, JI Minjun, GUO Jing, ZHANG Rong.
Application of the “virtual⁃real combination” experimental teaching model in Human Parasitology teaching: a case study of comprehensive schistosome experiments
[J]. Chinese Journal of Schistosomiasis Control, 2023, 35(2): 180-.
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[11] |
ZENG Ting, LÜ Shan, TIAN Liguang, LI Shizhu, SUN Leping, JIA Tiewu.
Temporal trends in disease burden of major human parasitic diseases in China from 1990 to 2019
[J]. Chinese Journal of Schistosomiasis Control, 2023, 35(1): 7-.
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[12] |
ZHOU Xia, LI Yuanyuan, XIA Chaoming.
Exploration and practice of process assessment in Human Parasitology teaching for international medical students
[J]. Chinese Journal of Schistosomiasis Control, 2023, 35(1): 82-.
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[13] |
WANG Yi, LI Cheng⁃yuan, ZHANG Jia⁃yao, HUANG Yi⁃xin, YANG Kun, LIU Yao⁃bao.
Construction of a human health literacy indicator system for prevention of parasitic diseases based on Delphi method
[J]. Chinese Journal of Schistosomiasis Control, 2022, 34(6): 616-.
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[14] |
LI Lu, WANG Qiang, XU Jing.
Application of integrated species distribution models in parasitic diseases prevention and control: a review
[J]. Chinese Journal of Schistosomiasis Control, 2022, 34(6): 659-.
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[15] |
SHI Liang, ZHANG Jian⁃feng, LI Wei, YANG Kun.
Artificial intelligence facilitates tropical infectious disease control and research
[J]. Chinese Journal of Schistosomiasis Control, 2022, 34(5): 445-.
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