Chang Hu

2.7k total citations · 3 hit papers
43 papers, 1.6k citations indexed

About

Chang Hu is a scholar working on Epidemiology, Infectious Diseases and Nephrology. According to data from OpenAlex, Chang Hu has authored 43 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Epidemiology, 10 papers in Infectious Diseases and 7 papers in Nephrology. Recurrent topics in Chang Hu's work include Sepsis Diagnosis and Treatment (11 papers), COVID-19 Clinical Research Studies (7 papers) and Long-Term Effects of COVID-19 (6 papers). Chang Hu is often cited by papers focused on Sepsis Diagnosis and Treatment (11 papers), COVID-19 Clinical Research Studies (7 papers) and Long-Term Effects of COVID-19 (6 papers). Chang Hu collaborates with scholars based in China, United States and United Kingdom. Chang Hu's co-authors include Zhiyong Peng, Yiming Li, Jianguo Li, Linjie Luo, Fang Fang, Guqin Zhang, Huaqin Pan, Zhiyong Peng, Yongfeng Chen and Yue Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Kidney International and Critical Care Medicine.

In The Last Decade

Chang Hu

37 papers receiving 1.6k citations

Hit Papers

Clinical features and short-term outcomes of 221 patients... 2020 2026 2022 2024 2020 2023 2025 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chang Hu China 14 680 385 287 254 252 43 1.6k
Yan Qin China 13 819 1.2× 436 1.1× 279 1.0× 165 0.6× 136 0.5× 59 1.7k
Luwen Wang China 16 516 0.8× 237 0.6× 449 1.6× 231 0.9× 198 0.8× 27 1.4k
Zili Zhang China 18 967 1.4× 445 1.2× 447 1.6× 335 1.3× 287 1.1× 49 2.4k
Xianghong Yang China 17 356 0.5× 158 0.4× 188 0.7× 144 0.6× 118 0.5× 44 931
Chen Dong China 22 1.1k 1.6× 488 1.3× 602 2.1× 676 2.7× 231 0.9× 76 2.6k
Zhao Wu China 12 1.0k 1.5× 648 1.7× 279 1.0× 212 0.8× 299 1.2× 28 1.9k
Ιrene Karampela Greece 26 330 0.5× 121 0.3× 493 1.7× 478 1.9× 160 0.6× 90 1.9k
Xiaowei Yan China 18 952 1.4× 509 1.3× 307 1.1× 138 0.5× 245 1.0× 76 2.1k
Haizhou Wang China 20 1.3k 1.9× 589 1.5× 372 1.3× 300 1.2× 327 1.3× 62 2.5k
Xiaoxin Wu China 18 1.3k 2.0× 678 1.8× 367 1.3× 486 1.9× 331 1.3× 87 2.5k

Countries citing papers authored by Chang Hu

Since Specialization
Citations

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

Fields of papers citing papers by Chang Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chang Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Chang Hu. A scholar is included among the top collaborators of Chang Hu 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 Chang Hu. Chang Hu 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
3.
Hu, Chang, et al.. (2025). How sports-implied packaging of protein powder products enhances the purchase intention of Generation Z: evidence from multiple experiments. Frontiers in Nutrition. 12. 1645614–1645614. 4 indexed citations
5.
Chen, Xinyi, Wenying Huang, & Chang Hu. (2025). Associations of perceived teacher–student relationship and friendship quality with adolescents' interest in physical education: a latent profile analysis. Frontiers in Sports and Active Living. 7. 1677083–1677083.
6.
Huang, Wenying, Bin Chen, & Chang Hu. (2025). The latent profile structure of negative emotion in female college students and its impact on eating behavior: the mediating role of physical exercise. Frontiers in Public Health. 13. 1663474–1663474. 13 indexed citations breakdown →
7.
Hu, Chang, et al.. (2025). The impact of weight self-stigma on appearance anxiety among female college students: a variable-centered and person-centered analysis. Frontiers in Public Health. 13. 1709480–1709480. 3 indexed citations
8.
Huang, Wenying, Bin Chen, & Chang Hu. (2025). Exploring self-rated health, physical activity, and social anxiety among female Chinese university students: a variable- and person-centered analysis. Frontiers in Public Health. 13. 1681504–1681504. 7 indexed citations
9.
Hu, Fen, Ying Wang, Chang Hu, et al.. (2024). Kotter’s 8-step change model to improve hand hygiene compliance in intensive care unit: A 41-month prospective longitudinal quality improvement study. Intensive and Critical Care Nursing. 87. 103877–103877. 1 indexed citations
10.
Hu, Chang, et al.. (2023). Clostridioides difficile infection after extracorporeal membrane oxygenation support for acute myocardial infarction: a case report. Frontiers in Medicine. 10. 1333209–1333209. 1 indexed citations
11.
Li, Ke, Han Gao, Chang Hu, et al.. (2023). Identification of potential diagnostic and prognostic biomarkers for sepsis based on machine learning. Computational and Structural Biotechnology Journal. 21. 2316–2331. 6 indexed citations
12.
Li, Yiming, Chang Hu, Jing Zhang, et al.. (2023). Fibroblastic reticular cell-derived exosomes are a promising therapeutic approach for septic acute kidney injury. Kidney International. 105(3). 508–523. 24 indexed citations
13.
Hu, Chang, Qing Tan, Yiming Li, et al.. (2022). Application of interpretable machine learning for early prediction of prognosis in acute kidney injury. Computational and Structural Biotechnology Journal. 20. 2861–2870. 32 indexed citations
14.
Li, Yiming, et al.. (2022). The potential biomarker TIFA regulates pyroptosis in sepsis-induced acute kidney injury. International Immunopharmacology. 115. 109580–109580. 13 indexed citations
15.
Hu, Chang, Yiming Li, Shou Zhen Wang, & Zhiyong Peng. (2022). Application of Machine Learning for Clinical Subphenotype Identification in Sepsis. Infectious Diseases and Therapy. 11(5). 1949–1964. 13 indexed citations
16.
Hu, Chang, Lu Li, Yiming Li, et al.. (2022). Explainable Machine-Learning Model for Prediction of In-Hospital Mortality in Septic Patients Requiring Intensive Care Unit Readmission. Infectious Diseases and Therapy. 11(4). 1695–1713. 26 indexed citations
17.
Li, Ziang, et al.. (2021). Bioinformatic Analysis of Prognostic and Immune-Related Genes in Pancreatic Cancer. Computational and Mathematical Methods in Medicine. 2021. 1–23. 5 indexed citations
18.
Yang, Xiao, Zhifeng Li, Binbin Wang, et al.. (2021). Prognosis and antibody profiles in survivors of critical illness from COVID-19: a prospective multicentre cohort study. British Journal of Anaesthesia. 128(3). 491–500. 11 indexed citations
19.
Wang, Dawei, Yimei Yin, Chang Hu, et al.. (2020). Clinical course and outcome of 107 patients infected with the novel coronavirus, SARS-CoV-2, discharged from two hospitals in Wuhan, China. Critical Care. 24(1). 188–188. 252 indexed citations
20.
Zhang, Guqin, Chang Hu, Linjie Luo, et al.. (2020). Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan, China. Journal of Clinical Virology. 127. 104364–104364. 507 indexed citations breakdown →

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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