Yongjiang Tang

673 total citations
32 papers, 494 citations indexed

About

Yongjiang Tang is a scholar working on Pulmonary and Respiratory Medicine, Internal Medicine and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Yongjiang Tang has authored 32 papers receiving a total of 494 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Pulmonary and Respiratory Medicine, 10 papers in Internal Medicine and 8 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Yongjiang Tang's work include Venous Thromboembolism Diagnosis and Management (10 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (7 papers) and Respiratory Support and Mechanisms (5 papers). Yongjiang Tang is often cited by papers focused on Venous Thromboembolism Diagnosis and Management (10 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (7 papers) and Respiratory Support and Mechanisms (5 papers). Yongjiang Tang collaborates with scholars based in China, Hong Kong and United States. Yongjiang Tang's co-authors include Yulin Feng, Haixia Zhou, Jun Xiao, Hui Y. Lan, Chen Yang, Xiao‐Ming Meng, Shuk‐Man Ka, Xiao-Ru Huang, David J. Nikolic‐Paterson and Shuang Wang and has published in prestigious journals such as Scientific Reports, Medicine and Thrombosis and Haemostasis.

In The Last Decade

Yongjiang Tang

28 papers receiving 491 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yongjiang Tang China 11 146 118 97 95 83 32 494
B. Imbert France 11 87 0.6× 51 0.4× 116 1.2× 116 1.2× 70 0.8× 38 477
Zeki Öngen Türkiye 13 102 0.7× 123 1.0× 93 1.0× 46 0.5× 220 2.7× 55 608
Beau M. Hawkins United States 13 232 1.6× 61 0.5× 224 2.3× 128 1.3× 235 2.8× 42 705
Frank Brosstad Norway 16 150 1.0× 42 0.4× 138 1.4× 119 1.3× 172 2.1× 41 617
Weijuan Li China 11 54 0.4× 152 1.3× 64 0.7× 29 0.3× 294 3.5× 35 759
Honglin Zhao China 12 103 0.7× 126 1.1× 93 1.0× 34 0.4× 93 1.1× 45 548
Vasiliki Karlaftis Australia 11 63 0.4× 54 0.5× 86 0.9× 46 0.5× 60 0.7× 24 443
Jung Kee Chung South Korea 12 137 0.9× 65 0.6× 264 2.7× 43 0.5× 41 0.5× 48 481
Claudia Yuste Spain 15 99 0.7× 128 1.1× 114 1.2× 10 0.1× 60 0.7× 41 724
So Yeon Oh South Korea 12 87 0.6× 34 0.3× 63 0.6× 52 0.5× 21 0.3× 40 375

Countries citing papers authored by Yongjiang Tang

Since Specialization
Citations

This map shows the geographic impact of Yongjiang Tang'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 Yongjiang Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yongjiang Tang more than expected).

Fields of papers citing papers by Yongjiang Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yongjiang Tang. 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 Yongjiang Tang. The network helps show where Yongjiang Tang may publish in the future.

Co-authorship network of co-authors of Yongjiang Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Yongjiang Tang. A scholar is included among the top collaborators of Yongjiang Tang 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 Yongjiang Tang. Yongjiang Tang 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.
Tang, Yongjiang, et al.. (2025). The association between serum albumin levels and metabolic syndrome based on the NHANES and two sample Mendelian randomization study. Scientific Reports. 15(1). 2861–2861. 2 indexed citations
2.
Tang, Yongjiang, et al.. (2025). Comprehensive characteristics of pulmonary antineutrophil cytoplasmic antibody-associated vasculitis and the development of a predictive nomogram for mortality. International Immunopharmacology. 147. 113986–113986. 2 indexed citations
4.
Yang, Yanlian, Guangming Wang, & Yongjiang Tang. (2024). Correlation of miRNAs with infarct volume in patients with acute ischemic stroke: A systematic review. Medicine. 103(50). e40728–e40728.
5.
Tang, Yongjiang, et al.. (2023). Causal relationship between Type 1 diabetes and osteoporosis and fracture occurrence: a two-sample Mendelian randomization analysis. Osteoporosis International. 34(6). 1111–1117. 11 indexed citations
6.
Li, Xiaoqian, Xingyu Xiong, Zongan Liang, & Yongjiang Tang. (2023). A machine learning diagnostic model for Pneumocystis jirovecii pneumonia in patients with severe pneumonia. Internal and Emergency Medicine. 18(6). 1741–1749. 6 indexed citations
7.
Zhou, Haixia, et al.. (2023). Pulmonary CT imaging findings in fat embolism syndrome: case series and literature review. Clinical Medicine. 23(1). 88–93. 7 indexed citations
9.
Hu, Yuehong, Xiaoqian Li, Haixia Zhou, et al.. (2020). Comparison between the Khorana prediction score and Caprini risk assessment models for assessing the risk of venous thromboembolism in hospitalized patients with cancer: a retrospective case control study. Interactive Cardiovascular and Thoracic Surgery. 31(4). 454–460. 8 indexed citations
12.
Tang, Yongjiang, Mingke Zhang, Yulin Feng, & Binmiao Liang. (2016). The measurement of lung volumes using body plethysmography and helium dilution methods in COPD patients: a correlation and diagnosis analysis. Scientific Reports. 6(1). 37550–37550. 13 indexed citations
13.
Wang, Shuang, Xiao‐Ming Meng, Yee-Yung Ng, et al.. (2015). TGF-β/Smad3 signalling regulates the transition of bone marrow-derived macrophages into myofibroblasts during tissue fibrosis. Oncotarget. 7(8). 8809–8822. 196 indexed citations
14.
Zhou, Haixia, Xuemei Ou, Yongjiang Tang, Lan Wang, & Yulin Feng. (2015). Advanced Chronic Obstructive Pulmonary Disease. Chinese Medical Journal. 128(21). 2952–2959. 17 indexed citations
15.
Tang, Yongjiang, Jun Xiao, Xiao Ru Huang, et al.. (2014). Latent Transforming Growth Factor-β1 Protects against Bleomycin-Induced Lung Injury in Mice. American Journal of Respiratory Cell and Molecular Biology. 51(6). 761–771. 17 indexed citations
16.
Zhou, Haixia, Lan Wang, Yongjiang Tang, et al.. (2013). Validation of a Venous Thromboembolism Risk Assessment Model in Hospitalized Chinese Patients: A Case-Control Study. Journal of Atherosclerosis and Thrombosis. 21(3). 261–272. 29 indexed citations
17.
Zhou, Haixia, Liqing Peng, Yan Yu, et al.. (2012). Validation of the Caprini risk assessment model in Chinese hospitalized patients with venous thromboembolism. Thrombosis Research. 130(5). 735–740. 41 indexed citations
18.
Zhou, Haixia, et al.. (2011). Antidepressant Drugs and Risk of Venous Thromboembolism: A Case Report and Literature Review. Klinik Psikofarmakoloji Bülteni-Bulletin of Clinical Psychopharmacology. 21(3). 237–241. 2 indexed citations
19.
Chen, Hong, Binmiao Liang, Zhibo Xu, et al.. (2011). Long-term non-invasive positive pressure ventilation in severe stable chronic obstructive pulmonary disease: a meta-analysis.. PubMed. 124(23). 4063–70. 9 indexed citations
20.
Prakash, Kunal, Yongjiang Tang, Alan P. Kozikowski, et al.. (2002). Synthesis and Biological Activity of Novel Neuroprotective Diketopiperazines. Bioorganic & Medicinal Chemistry. 10(9). 3043–3048. 39 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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