Hui-Ling Chan

416 citations
17 papers · 286 · h-index 7

Impact in

Papers in

Hui-Ling Chan

17 papers receiving 280 citations

Peers

Hui-Ling Chan
Comparison fields: 5 of 84
  • Pollution 57
  • Industrial and Manufacturing Engineering 39
  • Cognitive Neuroscience 86
  • Developmental and Educational Psychology 34
  • Neurology 19
Replace Dantong Zhu with:
Dantong Zhu United States
Kornél Németh Hungary
Dian Yu United States
Muriel Panouillères France
Meng Du China
Francisco Nieto-Escámez Spain
ZhongQuan Yi China
Kazunori Morikawa Japan
Stephanie Juran Germany
Samaneh Nemati United States
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Citations per field
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Citations per year

Countries citing papers authored by Hui-Ling Chan

Since Specialization
Citations

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

Fields of papers citing papers by Hui-Ling Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hui-Ling Chan. 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 Hui-Ling Chan. The network helps show where Hui-Ling Chan may publish in the future.

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 201869
2 201965
3 201142
4 200637
5 200517
6 202312
7 20228
8 20216
9 20126
10 20245
11 20244
12 20154
13 20124
14 20153
15 20222
16
Observations on the mechanisms of adaptation to the low protein intakes.
19661
17 20111

About Hui-Ling Chan

Hui-Ling Chan is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology, Molecular Biology, Social Psychology and Psychiatry and Mental health, having authored 17 papers that have together received 286 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (8 papers), Neural dynamics and brain function (5 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (3 papers), EEG and Brain-Computer Interfaces (3 papers), Psychosomatic Disorders and Their Treatments (2 papers), Recycling and Waste Management Techniques (1 paper), Mental Health and Psychiatry (1 paper) and Neuroscience and Neural Engineering (1 paper). The work is most often cited by research in Pollution (57 citations), Industrial and Manufacturing Engineering (39 citations), Cognitive Neuroscience (86 citations), Developmental and Educational Psychology (34 citations) and Neurology (19 citations). Hui-Ling Chan has collaborated with scholars based in Taiwan, Japan and Singapore. Frequent co-authors include Yong‐Sheng Chen, Chia‐Yi Cheng, Po‐Chih Kuo, Chuen–Tsai Sun, Sarah Cook, Hendrik Schäfer, Soroush Abolfathi, Jonathan Pearson, Gary D. Bending and Li‐Fen Chen. Their work appears in journals such as Journal of Neural Engineering, Scientific Reports, Computers & Education, Frontiers in Neuroinformatics and Journal of Pain.

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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