[1] |
Zhang Peize, Gao Qian, Deng Guofang.
[18F]FDT-PET-CT technology that may bring revolutionary changes to tuberculosis clinical research
[J]. Chinese Journal of Antituberculosis, 2025, 47(3): 262-265.
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[2] |
Yan Guangxuan, Wang Xueyu, Wang Yujin, Lan Tinglong, Nie Wenjuan.
Diagnostic value of using metagenomic second-generation sequencing on suspected osteoarticular tuberculosis patients
[J]. Chinese Journal of Antituberculosis, 2025, 47(2): 175-180.
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[3] |
Chen Jifei, Huang Lihua, Luo Lanbo, Sui Wenxian, Pang Yu, Liu Aimei.
Evaluation the efficacy of tongue swab-based PCR fluorescence probe method for pulmonary tuberculosis
[J]. Chinese Journal of Antituberculosis, 2025, 47(1): 51-60.
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[4] |
Zhong Lingshan, Wang Li, Zhang Shuo, Li Nan, Yang Qingyuan, Ding Wenlong, Chen Xingzhi, Huang Chencui, Xing Zhiheng.
A machine learning model based on CT images combined with radiomics and semantic features for diagnosis of nontuberculous mycobacterium lung disease and pulmonary tuberculosis
[J]. Chinese Journal of Antituberculosis, 2024, 46(9): 1042-1049.
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[5] |
Chen Shuangshuang, Tian Lili, Wang Nenhan, Yang Xinyu, Zhao Yanfeng, Li Chuanyou, Dai Xiaowei.
Analysis of in vitro antibacterial effects of 17 antibiotics against rapidly growing mycobacteria in the Beijing area
[J]. Chinese Journal of Antituberculosis, 2024, 46(9): 1056-1062.
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[6] |
Wang Biao, Liu Yuhong, Sun Yuxian, Zhang Lijie, Li Zhili, Shu Wei.
Investigation and analysis of laboratory diagnostic capabilities in tuberculosis-designated hospitals in China
[J]. Chinese Journal of Antituberculosis, 2024, 46(9): 1089-1097.
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[7] |
Li Wenhan, Yang Jing, Li Chunhua.
Research progress of artificial intelligence in pulmonary tuberculosis imaging diagnosis and drug resistance prediction
[J]. Chinese Journal of Antituberculosis, 2024, 46(9): 1098-1103.
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[8] |
Xue Yi, Liang Qian, Qi Haoran, Liang Ruixia, Huang Hairong.
Reliability analysis of rifampicin-resistance detected by different diagnostics as a predictor for multidrug-resistant tuberculosis
[J]. Chinese Journal of Antituberculosis, 2024, 46(8): 892-896.
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[9] |
Jia Hongyan, Fan Jun, Sun Qi, Song Ruixue, Du Boping, Dong Jing, Wang Yingchao, Xing Aiying, Zhu Chuanzhi, Li Zihui, Pan Liping.
Comparison of QuantiFERON-TB Gold Plus with QuantiFERON-TB Gold In-Tube assay in auxiliary diagnosis of osteoarticular tuberculosis
[J]. Chinese Journal of Antituberculosis, 2024, 46(6): 648-653.
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[10] |
Wang Liyan, Zhou Hui, Wu Qian, Hao Xiaogang, Lu Bingxin, Chen Bin.
Evaluation of the implementation effect of the “Zero Burden” strategy for diagnosis and treatment of pulmonary tuberculosis in Longyou County, Zhejiang Province
[J]. Chinese Journal of Antituberculosis, 2024, 46(4): 418-423.
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[11] |
Qin Liyi, Lyu Pingxin, Guo Lin, Qian Lingjun, Xiao Qian, Yang Yang, Shang Yuanyuan, Jia Junnan, Chu Naihui, Liu Yuanming, Li Weimin.
Deep learning to determine the healing status of pulmonary tuberculosis lesions on CT images
[J]. Chinese Journal of Antituberculosis, 2024, 46(3): 272-278.
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[12] |
Liu Xueyan, Wang Fang, Li Chunhua, Tang Guangxiao, Zheng Jiaofeng, Wang Huiqiu, Li Yurui, Wang Jia’nan, Shu Weiqiang, Lyu Shengxiu.
Construction and evaluation of a CT-based deep learning model for the auxiliary diagnosis of secondary tuberculosis
[J]. Chinese Journal of Antituberculosis, 2024, 46(3): 279-287.
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[13] |
Yi Wanqing, Zheng Xueyi, Zhang Zhuang, Sun Weirong, Yuan Xiaodong.
Comparison of the performance of deep learning models ResNet18 and ResNet50 based on multiphase CT for the diagnosis of renal tuberculosis
[J]. Chinese Journal of Antituberculosis, 2024, 46(3): 288-293.
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[14] |
Pan Ben, Liang Changhua, Han Dongming, Cui Junwei, Yao Yangyang, Wei Zhengqi, Zhen Siyu, Wei Hanyu, Yang Xinmiao.
Model construction and validation for predicting active drug-resistant pulmonary tuberculosis using combined CT radiomics and clinical features
[J]. Chinese Journal of Antituberculosis, 2024, 46(3): 294-301.
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[15] |
Yao Yangyang, Liang Changhua, Han Dongming, Cui Junwei, Pan Ben, Wang Huihui, Wei Zhengqi, Zhen Siyu, Wei Hanyu.
Differentiation of pulmonary tuberculosis and nontuberculous mycobacterial pulmonary disease based on computed tomography radiomics combined with clinical features
[J]. Chinese Journal of Antituberculosis, 2024, 46(3): 302-310.
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