Juanni Gong

640 total citations
46 papers, 449 citations indexed

About

Juanni Gong is a scholar working on Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine and Molecular Biology. According to data from OpenAlex, Juanni Gong has authored 46 papers receiving a total of 449 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Pulmonary and Respiratory Medicine, 19 papers in Cardiology and Cardiovascular Medicine and 10 papers in Molecular Biology. Recurrent topics in Juanni Gong's work include Pulmonary Hypertension Research and Treatments (27 papers), Circular RNAs in diseases (8 papers) and Cardiovascular Function and Risk Factors (7 papers). Juanni Gong is often cited by papers focused on Pulmonary Hypertension Research and Treatments (27 papers), Circular RNAs in diseases (8 papers) and Cardiovascular Function and Risk Factors (7 papers). Juanni Gong collaborates with scholars based in China, Australia and United States. Juanni Gong's co-authors include Yuanhua Yang, Xiaojuan Guo, Zhenguo Zhai, Ran Miao, Min-Fu Yang, Jifeng Li, Xiaoying Xi, Yidan Li, Dong Leng and Ying H. Shen and has published in prestigious journals such as CHEST Journal, Critical Care Medicine and European Respiratory Journal.

In The Last Decade

Juanni Gong

42 papers receiving 443 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Juanni Gong China 12 266 162 151 129 85 46 449
Xue Yu China 11 189 0.7× 126 0.8× 67 0.4× 44 0.3× 30 0.4× 42 412
Hui‐Li Gan China 10 197 0.7× 185 1.1× 46 0.3× 40 0.3× 68 0.8× 24 305
Nanette R. Reed United States 9 361 1.4× 163 1.0× 116 0.8× 62 0.5× 42 0.5× 13 573
Michel Zupan France 5 95 0.4× 67 0.4× 124 0.8× 49 0.4× 30 0.4× 6 239
Porama Thanaporn United States 7 67 0.3× 121 0.7× 67 0.4× 45 0.3× 248 2.9× 9 452
Geerte L. Van Sluis Netherlands 7 67 0.3× 100 0.6× 58 0.4× 35 0.3× 255 3.0× 11 438
Annette Feussner Germany 10 57 0.2× 200 1.2× 59 0.4× 61 0.5× 160 1.9× 15 626
Hideto Ito Japan 12 154 0.6× 39 0.2× 114 0.8× 55 0.4× 17 0.2× 34 401
Dennis Göerlich Germany 5 119 0.4× 116 0.7× 82 0.5× 52 0.4× 67 0.8× 11 427
Eiji Furukoji Japan 10 85 0.3× 80 0.5× 59 0.4× 19 0.1× 72 0.8× 24 344

Countries citing papers authored by Juanni Gong

Since Specialization
Citations

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

Fields of papers citing papers by Juanni Gong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juanni Gong

This figure shows the co-authorship network connecting the top 25 collaborators of Juanni Gong. A scholar is included among the top collaborators of Juanni Gong 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 Juanni Gong. Juanni Gong 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.
Gong, Juanni, et al.. (2025). Assessing the effects of digitalization on the amenity of clean energy supply chains: Policy insights from OECD countries. Energy Economics. 143. 108273–108273. 3 indexed citations
2.
3.
He, Qin, et al.. (2025). Exploring the dynamic linkages between carbon trading market and smart technology indices: A multi-dimensional analysis of China's case. International Review of Economics & Finance. 102. 104360–104360. 2 indexed citations
4.
5.
Gong, Juanni, Jianjun Mao, Jifeng Li, et al.. (2023). Analysis of clinical features between active and inactive patients of Takayasu's arteritis with pulmonary arteries involvement. International Journal of Cardiology. 381. 88–93. 2 indexed citations
6.
Jiao, Xiaojing, Jiayu Liu, Wei Wang, et al.. (2023). Padua prediction score may be inappropriate for VTE risk assessment in hospitalized patients with acute respiratory conditions: A Chinese single-center cohort study. IJC Heart & Vasculature. 49. 101301–101301. 3 indexed citations
7.
Gong, Juanni, et al.. (2022). Pulmonary artery imaging with 68 Ga-FAPI-04 in patients with chronic thromboembolic pulmonary hypertension. Journal of Nuclear Cardiology. 30(3). 1166–1172. 4 indexed citations
8.
9.
Gong, Juanni, Yidan Li, Xiaojuan Guo, et al.. (2021). Expression of miR‐93‐5p as a Potential Predictor of the Severity of Chronic Thromboembolic Pulmonary Hypertension. BioMed Research International. 2021(1). 6634417–6634417. 10 indexed citations
10.
Yang, Yuanhua, Juanni Gong, Jifeng Li, et al.. (2021). Haemodynamic effects of riociguat in CTEPH and PAH: a 10-year observational study. ERJ Open Research. 7(3). 82–2021. 3 indexed citations
11.
Xing, Haiqun, Juanni Gong, Xiaojuan Guo, et al.. (2021). Imaging of cardiac fibroblast activation in patients with chronic thromboembolic pulmonary hypertension. European Journal of Nuclear Medicine and Molecular Imaging. 49(4). 1211–1222. 26 indexed citations
12.
Li, Yidan, Lirong Liang, Yuanhua Yang, et al.. (2021). Right Ventricular Function Predicts Adverse Clinical Outcomes in Patients With Chronic Thromboembolic Pulmonary Hypertension: A Three-Dimensional Echocardiographic Study. Frontiers in Medicine. 8. 697396–697396. 9 indexed citations
13.
Xi, Xiaoying, et al.. (2019). Value of 18F-FDG PET/CT in differentiating malignancy of pulmonary artery from pulmonary thromboembolism: a cohort study and literature review. International journal of cardiac imaging. 35(7). 1395–1403. 33 indexed citations
14.
Miao, Ran, Juanni Gong, Chun‐yang Zhang, et al.. (2019). Hsa_circ_0046159 is involved in the development of chronic thromboembolic pulmonary hypertension. Journal of Thrombosis and Thrombolysis. 49(3). 386–394. 24 indexed citations
15.
Xi, Xiaoying, Wei Gao, Xiaojuan Guo, et al.. (2019). Multiple cardiovascular involvements in Behçet’s disease: unique utility of 18F-FDG PET/CT in diagnosis and follow-up. European Journal of Nuclear Medicine and Molecular Imaging. 46(10). 2210–2211. 4 indexed citations
16.
Gong, Juanni, Yuanhua Yang, Zhanhong Ma, et al.. (2018). Clinical and imaging manifestations of Takayasu's arteritis with pulmonary hypertension: A retrospective cohort study in China. International Journal of Cardiology. 276. 224–229. 20 indexed citations
17.
Miao, Ran, et al.. (2018). [Analysis of significant microRNA associated with chronic thromboembolic pulmonary hypertension].. PubMed. 98(18). 1397–1402. 6 indexed citations
18.
Yang, Yuanhua, et al.. (2014). Risk factors of chronic thromboembolic pulmonary hypertension after acute pulmonary embolism. European Respiratory Journal. 44(Suppl 58). P2324–P2324. 1 indexed citations
19.
20.
Zhang, Shuai, Zhenguo Zhai, Yuanhua Yang, et al.. (2014). Pulmonary embolism risk stratification by European Society of Cardiology is associated with recurrent venous thromboembolism: Findings from a long-term follow-up study. International Journal of Cardiology. 202. 275–281. 10 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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