Yan Ma

81 papers receiving 1.3k citations

Peers

Yan Ma
Comparison fields: 5 of 156
  • Complementary and alternative medicine 226
  • Endocrine and Autonomic Systems 145
  • Experimental and Cognitive Psychology 259
  • Cognitive Neuroscience 376
  • Cardiology and Cardiovascular Medicine 207
Replace Shuzhen Li with:
Shuzhen Li China
Karina Rabello Casali Brazil
Jukka A. Lipponen Finland
Hung‐Wen Chiu Taiwan
Cheng‐Deng Kuo Taiwan
Przemysław Guzik Poland
Marco Laurino Italy
Michal Javorka Slovakia
K. Paul Joseph India
Vadim Zipunnikov United States
Yan Ma relative to Shuzhen Li China Shuzhen Li's profile →
Citations per field
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Shuzhen Li · 1×
Citations per year

Countries citing papers authored by Yan Ma

Since Specialization
Citations

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

Fields of papers citing papers by Yan Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yan Ma, 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 Yan Ma Line = papers co-authored together Yan Ma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 94 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016133
2 2017124
3 2020102
4 202279
5 201670
6 201955
7 201554
8 201653
9 201552
10 202051
11 201438
12 201735
13 201532
14 202129
15 201726
16 201925
17 201721
18 201421
19 201920
20 201920

About Yan Ma

Yan Ma is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology, Complementary and alternative medicine, Cardiology and Cardiovascular Medicine and Surgery, having authored 94 papers that have together received 1.4k indexed citations. Recurring topics across this work include Sleep and related disorders (14 papers), Sleep and Wakefulness Research (11 papers), Heart Rate Variability and Autonomic Control (10 papers), EEG and Brain-Computer Interfaces (9 papers), Obstructive Sleep Apnea Research (9 papers), Non-Invasive Vital Sign Monitoring (6 papers), Complex Systems and Time Series Analysis (6 papers) and Neural dynamics and brain function (6 papers). The work is most often cited by research in Complementary and alternative medicine (226 citations), Endocrine and Autonomic Systems (145 citations), Experimental and Cognitive Psychology (259 citations), Cognitive Neuroscience (376 citations) and Cardiology and Cardiovascular Medicine (207 citations). Yan Ma has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Kehua Zhou, Chung‐Kang Peng, Shuchen Sun, Albert C. Yang, Wenbin Shi, Gloria Y. Yeh, Peter M. Wayne, Ming Dong, Carol Mita and Jianping Liu. Their work appears in journals such as Sleep Medicine, PLoS ONE, Journal of Clinical Sleep Medicine, Scientific Reports and Frontiers of Medicine.

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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