Xiangmin Gao

735 total citations
30 papers, 440 citations indexed

About

Xiangmin Gao is a scholar working on Epidemiology, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, Xiangmin Gao has authored 30 papers receiving a total of 440 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Epidemiology, 10 papers in Cardiology and Cardiovascular Medicine and 5 papers in Surgery. Recurrent topics in Xiangmin Gao's work include Congenital Heart Disease Studies (12 papers), Pregnancy and preeclampsia studies (4 papers) and Cardiovascular Health and Risk Factors (4 papers). Xiangmin Gao is often cited by papers focused on Congenital Heart Disease Studies (12 papers), Pregnancy and preeclampsia studies (4 papers) and Cardiovascular Health and Risk Factors (4 papers). Xiangmin Gao collaborates with scholars based in China, United States and Norway. Xiangmin Gao's co-authors include Jinzhuang Mai, Yong Wu, Xiaoqing Liu, Zhiqiang Nie, Yanqiu Ou, Yanji Qu, Jian Zhuang, Shao Lin, Jimei Chen and Michael S. Bloom and has published in prestigious journals such as PLoS ONE, Environmental Pollution and The American Journal of Cardiology.

In The Last Decade

Xiangmin Gao

28 papers receiving 436 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiangmin Gao China 12 162 124 83 72 63 30 440
Jinzhuang Mai China 13 179 1.1× 146 1.2× 97 1.2× 115 1.6× 95 1.5× 35 550
Benjamin J. Harshfield United States 8 142 0.9× 48 0.4× 114 1.4× 34 0.5× 122 1.9× 10 816
Qun Huang China 11 116 0.7× 83 0.7× 160 1.9× 19 0.3× 111 1.8× 43 439
Verónica Perea Spain 15 101 0.6× 141 1.1× 154 1.9× 29 0.4× 23 0.4× 54 620
Deborah H. Glueck United States 14 65 0.4× 26 0.2× 77 0.9× 41 0.6× 73 1.2× 24 467
Michel Tournaire France 11 63 0.4× 202 1.6× 113 1.4× 67 0.9× 24 0.4× 39 686
Pingting Yang China 13 100 0.6× 134 1.1× 46 0.6× 45 0.6× 48 0.8× 40 437
Françoise Barbé France 15 37 0.2× 45 0.4× 132 1.6× 30 0.4× 39 0.6× 31 530
Alex C. Vidaeff United States 17 148 0.9× 25 0.2× 122 1.5× 54 0.8× 161 2.6× 59 668

Countries citing papers authored by Xiangmin Gao

Since Specialization
Citations

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

Fields of papers citing papers by Xiangmin Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiangmin Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Xiangmin Gao. A scholar is included among the top collaborators of Xiangmin Gao 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 Xiangmin Gao. Xiangmin Gao 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.
Qu, Yanji, Adela Jing Li, Xiaoqing Liu, et al.. (2023). Maternal serum neonicotinoids during early-mid pregnancy and congenital heart diseases in offspring: An exploratory study. Environmental Pollution. 342. 123046–123046. 16 indexed citations
2.
Qu, Yanji, Xin Deng, Shao Lin, et al.. (2022). Using Innovative Machine Learning Methods to Screen and Identify Predictors of Congenital Heart Diseases. Frontiers in Cardiovascular Medicine. 8. 797002–797002. 22 indexed citations
3.
Ou, Yanqiu, Michael S. Bloom, Jinzhuang Mai, et al.. (2022). Prenatal Detection of Congenital Heart Diseases Using Echocardiography: 12-Year Results of an Improving Program With 9782 Cases. Frontiers in Public Health. 10. 886262–886262. 3 indexed citations
4.
Qu, Yanji, Shao Lin, Jian Zhuang, et al.. (2020). First‐Trimester Maternal Folic Acid Supplementation Reduced Risks of Severe and Most Congenital Heart Diseases in Offspring: A Large Case‐Control Study. Journal of the American Heart Association. 9(13). e015652–e015652. 36 indexed citations
5.
Zhou, Long, Jinzhuang Mai, Ying Li, et al.. (2020). Triglyceride to high-density lipoprotein cholesterol ratio and risk of atherosclerotic cardiovascular disease in a Chinese population. Nutrition Metabolism and Cardiovascular Diseases. 30(10). 1706–1713. 20 indexed citations
6.
Qu, Yanji, Bo‐Yi Yang, Shao Lin, et al.. (2020). Associations of greenness with gestational diabetes mellitus: The Guangdong Registry of Congenital Heart Disease (GRCHD) study. Environmental Pollution. 266(Pt 2). 115127–115127. 26 indexed citations
7.
Nie, Zhiqiang, Yanqiu Ou, Michael S. Bloom, et al.. (2020). Maternal residential greenness and congenital heart defects in infants: A large case-control study in Southern China. Environment International. 142. 105859–105859. 18 indexed citations
8.
Qu, Yanji, Shao Lin, Michael S. Bloom, et al.. (2020). Maternal folic acid supplementation mediates the associations between maternal socioeconomic status and congenital heart diseases in offspring. Preventive Medicine. 143. 106319–106319. 9 indexed citations
9.
Gao, Xiangmin, Guixian Wu, Jian Chen, & Qingyan Zeng. (2020). Design and implementation of geological hazard monitoring system via the Internet of things. Arabian Journal of Geosciences. 13(21). 3 indexed citations
10.
Madani, Vahid, et al.. (2018). Life cycle experiences with micro-processor based relays and roadmap to sustainability. 1–13. 1 indexed citations
11.
Liu, Huanhuan, Xiangmin Gao, Long Zhou, et al.. (2018). Urinary sodium excretion and risk of cardiovascular disease in the Chinese population: a prospective study. Hypertension Research. 41(10). 849–855. 16 indexed citations
12.
13.
Qu, Yanji, Xiaoqing Liu, Jian Zhuang, et al.. (2016). Incidence of Congenital Heart Disease: The 9-Year Experience of the Guangdong Registry of Congenital Heart Disease, China. PLoS ONE. 11(7). e0159257–e0159257. 78 indexed citations
14.
Qu, Yanji, Xiaoqing Liu, Jinzhuang Mai, et al.. (2015). [Analysis of environmental risk factors in congenital heart defects].. PubMed. 47(3). 420–30. 2 indexed citations
15.
Ou, Yanqiu, Jinzhuang Mai, Jian Zhuang, et al.. (2015). Risk factors of different congenital heart defects in Guangdong, China. Pediatric Research. 79(4). 549–558. 52 indexed citations
16.
Mai, Jinzhuang, et al.. (2014). [Long term trends of blood lipid and glucose change in Guangzhou urban and rural natural population].. PubMed. 42(6). 515–9. 1 indexed citations
17.
Liu, Xiaoqing, Jinzhuang Mai, Xiangmin Gao, et al.. (2013). [Current prevalence rate of congenital heart disease in 12 month-old and younger infants among four regions of Guangdong province].. PubMed. 41(4). 337–40. 4 indexed citations
18.
19.
Gao, Xiangmin & Mingyong Pang. (2009). Visualizing Non-linear Ordinary Differential Dynamic System Using Simulink. 13. 589–593. 1 indexed citations
20.
Cheng, Tsung O., et al.. (2006). Impact of Dysglycemia, Body Mass Index, and Waist-to-Hip Ratio on the Prevalence of Systemic Hypertension in a Lean Chinese Population. The American Journal of Cardiology. 97(6). 839–842. 17 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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