Jonathan H. Chan
Impact in
- Health Informatics top 10%
- Nuclear and High Energy Physics top 10%
- Quantum Chromodynamics and Particle Interactions
- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Nuclear physics research studies
Papers in
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- Topic Modeling 6
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- Bioinformatics and Genomic Networks 9
- Gene expression and cancer classification 8
- Machine Learning in Bioinformatics 4
- Co-authors
- Pornchai Mongkolnam (12 shared papers)Worrawat Engchuan (9 shared papers)J. A. Kadyk (2 shared papers)G. H. Trilling (1 shared paper)G. Alexander (1 shared paper)P. B. Price (3 shared papers)Mark Chignell (5 shared papers)Asawin Meechai (7 shared papers)
In The Last Decade
Jonathan H. Chan
65 papers receiving 600 citations
Peers
Comparison fields: 5 of 119
- Health Informatics 16
- Nuclear and High Energy Physics 118
- Human-Computer Interaction 32
- Artificial Intelligence 150
- Rehabilitation 27
Countries citing papers authored by Jonathan H. Chan
This map shows the geographic impact of Jonathan H. 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 Jonathan H. Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan H. Chan more than expected).
Fields of papers citing papers by Jonathan H. Chan
This network shows the impact of papers produced by Jonathan H. 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 Jonathan H. Chan. The network helps show where Jonathan H. Chan may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan H. Chan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1971 | 100 | |
| 2 | 2020 | 85 | |
| 3 | 2018 | 25 | |
| 4 | 2015 | 25 | |
| 5 | 2015 | 24 | |
| 6 | 1975 | 23 | |
| 7 | 2021 | 23 | |
| 8 | 2017 | 21 | |
| 9 | 2009 | 20 | |
| 10 | 2020 | 16 | |
| 11 | 2015 | 15 | |
| 12 | 2024 | 14 | |
| 13 | 2018 | 12 | |
| 14 | 2020 | 12 | |
| 15 | 2015 | 12 | |
| 16 | 2023 | 10 | |
| 17 | 2016 | 10 | |
| 18 | 2010 | 9 | |
| 19 | 2016 | 9 | |
| 20 | 2016 | 8 |
About Jonathan H. Chan
Jonathan H. Chan is a scholar working on Artificial Intelligence, Molecular Biology, Information Systems, Computer Vision and Pattern Recognition and Signal Processing, having authored 71 papers that have together received 625 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (9 papers), Gene expression and cancer classification (8 papers), Topic Modeling (6 papers), Astro and Planetary Science (5 papers), COVID-19 diagnosis using AI (5 papers), Solar and Space Plasma Dynamics (5 papers), Machine Learning in Bioinformatics (4 papers) and Gait Recognition and Analysis (4 papers). The work is most often cited by research in Health Informatics (16 citations), Nuclear and High Energy Physics (118 citations), Human-Computer Interaction (32 citations), Artificial Intelligence (150 citations) and Rehabilitation (27 citations). Jonathan H. Chan has collaborated with scholars based in Thailand, Canada and Hong Kong. Frequent co-authors include Pornchai Mongkolnam, Worrawat Engchuan, J. A. Kadyk, G. H. Trilling, G. Alexander, P. B. Price, Mark Chignell, Asawin Meechai, Vajirasak Vanijja and Minho Lee. Their work appears in journals such as Journal of Bioinformatics and Computational Biology, IEEE Access, Heliyon, Physical Review Letters and PeerJ.
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.