Zhong Dong

1.6k citations
58 papers · 670 indexed · 1 hit paper · h-index 13

Zhong Dong

57 papers receiving 655 citations

Hit Papers

Overview of predictive maintenance based on digital twin ...13020232026202420254080120

Peers

Zhong Dong
Comparison fields: 5 of 144
  • Industrial and Manufacturing Engineering 71
  • Medical Laboratory Technology 9
  • Neurology 72
  • Endocrinology, Diabetes and Metabolism 71
  • Obstetrics and Gynecology 33
Replace Zhaoyi Chen with:
Zhaoyi Chen United States
Laura M. Roa Spain
José M. Celaya-Padilla Mexico
Carlo Ricciardi Italy
Jiawei Wang China
Yi Xie China
Daniel Ruíz Fernández Spain
Sakib Mahmud Bangladesh
Yao Sun United States
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Citations per year

Countries citing papers authored by Zhong Dong

Since Specialization
Citations

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

Fields of papers citing papers by Zhong Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Zhong Dong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Zhong Dong Line = papers co-authored together Zhong Dong links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20242
2 20232
3 20233
4 20213
5 20202
6 202019
7 20161
8 20161
9
A Practice of Mobile Learning Based on Cloud Computing.
20161
10 20157
11
[Change trend of birth weight of twins in China, 1995-2012].
20155
12
[Heritability of body mass index on Chinese adult twins from nine provinces/cities in China].
20151
13 20152
14 201512
15 201511
16 201514
17 201515
18 201311
19 201273
20 200928

About Zhong Dong

Zhong Dong is a scholar working on Obstetrics and Gynecology, Internal Medicine and Pediatrics, Perinatology and Child Health, having authored 58 papers that have together received 670 indexed citations. Recurring topics across this work include Obesity, Physical Activity, Diet (9 papers), Birth, Development, and Health (7 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers), Acute Ischemic Stroke Management (6 papers), Pregnancy and preeclampsia studies (5 papers), Genetic Associations and Epidemiology (5 papers), Vehicular Ad Hoc Networks (VANETs) (4 papers) and Mobile Ad Hoc Networks (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (71 citations), Medical Laboratory Technology (9 citations) and Neurology (72 citations). Zhong Dong has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Jun-Hua Duan, Yi‐An Zhu, Yian Zhu, Hang Li, Yize Xiao, Yan Guo, Catherine Chamberlain, Robert Hall, Damien Jolley and Yan Shi. Their work appears in journals such as PLoS ONE, The Science of The Total Environment and Journal of Hazardous Materials.

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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