Shiji Wu

7.8k total citations · 1 hit paper
47 papers, 4.6k citations indexed

About

Shiji Wu is a scholar working on Infectious Diseases, Epidemiology and Immunology. According to data from OpenAlex, Shiji Wu has authored 47 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Infectious Diseases, 18 papers in Epidemiology and 14 papers in Immunology. Recurrent topics in Shiji Wu's work include Tuberculosis Research and Epidemiology (11 papers), Mycobacterium research and diagnosis (10 papers) and Immune Cell Function and Interaction (10 papers). Shiji Wu is often cited by papers focused on Tuberculosis Research and Epidemiology (11 papers), Mycobacterium research and diagnosis (10 papers) and Immune Cell Function and Interaction (10 papers). Shiji Wu collaborates with scholars based in China, Canada and United States. Shiji Wu's co-authors include Minxia Zhang, Xiaoping Zhang, Meifang Han, Hongwu Wang, Xiaoyun Zhang, Haijing Yu, Shusheng Li, Tao Chen, Jianxin Song and Yong Cao and has published in prestigious journals such as Journal of Clinical Investigation, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Shiji Wu

43 papers receiving 4.5k citations

Hit Papers

Clinical and immunological features of severe and moderat... 2020 2026 2022 2024 2020 1000 2.0k 3.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Clinical and immunological features of severe and moderate coronavirus disease 2019
    2020 3.2k citations Guang Chen, Di Wu et al. Journal of Clinical Investigation profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shiji Wu China 18 3.4k 1.8k 787 580 567 47 4.6k
Hongwu Wang China 14 2.7k 0.8× 1.5k 0.9× 554 0.7× 423 0.7× 520 0.9× 37 3.8k
Yong Xiong China 22 3.2k 0.9× 1.6k 0.9× 457 0.6× 600 1.0× 577 1.0× 72 4.4k
Ziwei Hu China 9 3.4k 1.0× 1.9k 1.1× 459 0.6× 604 1.0× 412 0.7× 22 4.3k
Meifang Han China 23 2.9k 0.9× 1.6k 0.9× 739 0.9× 480 0.8× 693 1.2× 59 4.9k
Cuihong Xie China 9 3.4k 1.0× 1.9k 1.1× 443 0.6× 576 1.0× 434 0.8× 9 4.4k
Shuoqi Zhang China 8 3.4k 1.0× 1.9k 1.1× 437 0.6× 603 1.0× 396 0.7× 10 4.2k
Da Huang China 16 2.6k 0.8× 1.5k 0.8× 473 0.6× 496 0.9× 818 1.4× 78 4.0k
Haijing Yu China 9 2.7k 0.8× 1.6k 0.9× 425 0.5× 425 0.7× 445 0.8× 14 3.5k

Countries citing papers authored by Shiji Wu

Since Specialization
Citations

This map shows the geographic impact of Shiji Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shiji Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shiji Wu more than expected).

Fields of papers citing papers by Shiji Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shiji Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shiji Wu. The network helps show where Shiji Wu may publish in the future.

Co-authorship network of co-authors of Shiji Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Shiji Wu. A scholar is included among the top collaborators of Shiji Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shiji Wu. Shiji Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ming, Liang, Shiji Wu, Bing Ou, et al.. (2025). Discriminating Clear Cell From Non-Clear Cell Renal Cell Carcinoma: A Machine Learning Approach Using Contrast-enhanced Ultrasound Radiomics. Ultrasound in Medicine & Biology. 51(8). 1361–1369.
2.
Wang, Xiaochen, Kaijun Jiang, Wanli Xing, et al.. (2025). Clustering Mycobacterium tuberculosis-specific CD154+CD4+ T cells for distinguishing tuberculosis disease from infection based on single-cell RNA-seq analysis. Journal of Infection. 90(4). 106449–106449. 1 indexed citations
3.
4.
Wei, Wei, Yun Wang, Ting Wang, et al.. (2024). Machine Learning for Early Discrimination Between Lung Cancer and Benign Nodules Using Routine Clinical and Laboratory Data. Annals of Surgical Oncology. 31(12). 7738–7749. 7 indexed citations
5.
Luo, Ying, Ying Xue, Guoxing Tang, et al.. (2021). Lymphocyte-Related Immunological Indicators for Stratifying Mycobacterium tuberculosis Infection. Frontiers in Immunology. 12. 658843–658843. 17 indexed citations
6.
Luo, Ying, Ying Xue, Qun Lin, et al.. (2021). Lymphocyte Non-Specific Function Detection Facilitating the Stratification of Mycobacterium tuberculosis Infection. Frontiers in Immunology. 12. 641378–641378. 9 indexed citations
7.
Peng, Jing, Juan Song, Feng Wang, et al.. (2021). Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting. Frontiers in Cellular and Infection Microbiology. 11. 650163–650163. 6 indexed citations
8.
Hou, Hongyan, Yandi Zhang, Guoxing Tang, et al.. (2021). Immunologic memory to SARS-CoV-2 in convalescent COVID-19 patients at 1 year postinfection. Journal of Allergy and Clinical Immunology. 148(6). 1481–1492.e2. 33 indexed citations
9.
Luo, Ying, Ying Xue, Qun Lin, et al.. (2021). Diagnostic Model for Discrimination Between Tuberculous Meningitis and Bacterial Meningitis. Frontiers in Immunology. 12. 731876–731876. 9 indexed citations
10.
Tang, Guoxing, Yuan Xu, Qun Lin, et al.. (2021). Using Routine Laboratory Markers and Immunological Indicators for Predicting Pneumocystis jiroveci Pneumonia in Immunocompromised Patients. Frontiers in Immunology. 12. 652383–652383. 25 indexed citations
11.
Wang, Feng, Hongyan Hou, Ying Luo, et al.. (2020). The laboratory tests and host immunity of COVID-19 patients with different severity of illness. JCI Insight. 5(10). 372 indexed citations
12.
Chen, Guang, Di Wu, Wei Guo, et al.. (2020). Clinical and immunological features of severe and moderate coronavirus disease 2019. Journal of Clinical Investigation. 130(5). 2620–2629. 3242 indexed citations breakdown →
13.
Luo, Ying, Ying Xue, Liyan Mao, et al.. (2020). Diagnostic utility of pleural fluid T-SPOT and interferon-gamma for tuberculous pleurisy: A two-center prospective cohort study in China. International Journal of Infectious Diseases. 99. 515–521. 9 indexed citations
14.
Wang, Feng, Hongyan Hou, Ting Wang, et al.. (2020). Establishing a model for predicting the outcome of COVID-19 based on combination of laboratory tests. Travel Medicine and Infectious Disease. 36. 101782–101782. 32 indexed citations
15.
Wu, Shiji, Feng Wang, Jin Huang, et al.. (2019). Evaluation of the automated indirect immunofluorescence test for anti-dsDNA antibodies. Clinica Chimica Acta. 498. 143–147. 3 indexed citations
16.
Wang, Feng, Jing Yu, Yu Zhou, et al.. (2018). The Use of TB-Specific Antigen/Phytohemagglutinin Ratio for Diagnosis and Treatment Monitoring of Extrapulmonary Tuberculosis. Frontiers in Immunology. 9. 1047–1047. 23 indexed citations
17.
Wang, Feng, Lie Mao, Hongyan Hou, et al.. (2016). The source of Mycobacterium tuberculosis-specific IFN-γ production in peripheral blood mononuclear cells of TB patients. International Immunopharmacology. 32. 39–45. 7 indexed citations
18.
Hou, Hongyan, Weiyong Liu, Shiji Wu, et al.. (2014). Tim-3 Negatively Mediates Natural Killer Cell Function in LPS-Induced Endotoxic Shock. PLoS ONE. 9(10). e110585–e110585. 32 indexed citations
19.
Wang, Feng, Shuanglin Liu, Shiji Wu, et al.. (2011). Blocking TREM-1 signaling prolongs survival of mice with Pseudomonas aeruginosa induced sepsis. Cellular Immunology. 272(2). 251–258. 48 indexed citations
20.
Peng, Jing, Liming Cheng, Botao Yin, et al.. (2011). Development of an economic and efficient strategy to detect HBsAg: Application of “gray-zones” in ELISA and combined use of several detection assays. Clinica Chimica Acta. 412(23-24). 2046–2051. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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