Ching-Hua Chen

26 papers receiving 346 citations

Peers

Ching-Hua Chen
Comparison fields: 5 of 77
  • Applied Psychology 38
  • Human-Computer Interaction 25
  • Experimental and Cognitive Psychology 54
  • Artificial Intelligence 88
  • Health Information Management 10
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Hillol Sarker United States
Temiloluwa Prioleau United States
Alina Trifan Portugal
Xiaopeng Lu United States
Jon Arambarri Spain
Mario Alberto Chapa Martell Japan
Enrique Dorronzoro Spain
Gonzalo J. Martinez United States
Alban Maxhuni Italy
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Citations per field
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Citations per year

Countries citing papers authored by Ching-Hua Chen

Since Specialization
Citations

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

Fields of papers citing papers by Ching-Hua Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching-Hua Chen. 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 Ching-Hua Chen. The network helps show where Ching-Hua Chen may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201998
2 202061
3 202056
4 202129
5 201829
6 201813
7 20179
8 20179
9 20228
10 20217
11 20216
12 20195
13 20185
14 20194
15 20233
16 20173
17 20213
18 20213
19 20182
20
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20192

About Ching-Hua Chen

Ching-Hua Chen is a scholar working on Artificial Intelligence, General Health Professions, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Molecular Biology, having authored 28 papers that have together received 362 indexed citations. Recurring topics across this work include Mobile Health and mHealth Applications (4 papers), Behavioral Health and Interventions (3 papers), Semantic Web and Ontologies (3 papers), Culinary Culture and Tourism (3 papers), Biomedical Text Mining and Ontologies (3 papers), Context-Aware Activity Recognition Systems (2 papers), Nutritional Studies and Diet (2 papers) and Digital Mental Health Interventions (2 papers). The work is most often cited by research in Applied Psychology (38 citations), Human-Computer Interaction (25 citations), Experimental and Cognitive Psychology (54 citations), Artificial Intelligence (88 citations) and Health Information Management (10 citations). Ching-Hua Chen has collaborated with scholars based in United States, United Kingdom and Taiwan. Frequent co-authors include Deborah L. McGuinness, Oshani Seneviratne, Mohammed J. Zaki, James Codella, Varun Mishra, Yu Chen, Grace Chen, Jeffrey M. Rogers, Sougata Sen and David Kotz. Their work appears in journals such as Frontiers in Psychiatry, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Journal of Behavioral Medicine, IBM Journal of Research and Development and Journal of Biomedical Semantics.

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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