I‐Jen Chiang
Impact in
- Neurology top 10%
- Traumatic Brain Injury and Neurovascular Disturbances
- Brain Tumor Detection and Classification
- Intracerebral and Subarachnoid Hemorrhage Research
Papers in
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- Topic Modeling 5
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- Data Mining Algorithms and Applications 9
- Co-authors
- Chun-Chih Liao (15 shared papers)Furen Xiao (15 shared papers)Jau‐Min Wong (16 shared papers)Jane Yung-jen Hsu (5 shared papers)Tsau Young Lin (2 shared papers)Ajit Kumar (6 shared papers)Thomas Mon-Hsian Hsieh (2 shared papers)Yimin Liu (1 shared paper)
- Journals
- Journal of Biomedical Informatics (2 papers)Computers in Biology and Medicine (2 papers)Applied Intelligence (1 paper)Clinical Neurology and Neurosurgery (1 paper)Human Pathology (1 paper)
- Partner nations
- TaiwanUnited StatesIndia
In The Last Decade
I‐Jen Chiang
51 papers receiving 545 citations
Peers
Comparison fields: 5 of 119
- Neurology 59
- Health Informatics 8
- Neurology 80
- Computer Vision and Pattern Recognition 103
- Health Information Management 21
Countries citing papers authored by I‐Jen Chiang
This map shows the geographic impact of I‐Jen Chiang'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 I‐Jen Chiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites I‐Jen Chiang more than expected).
Fields of papers citing papers by I‐Jen Chiang
This network shows the impact of papers produced by I‐Jen Chiang. 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 I‐Jen Chiang. The network helps show where I‐Jen Chiang may publish in the future.
Co-authors
The 25 scholars most cited alongside I‐Jen Chiang, 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 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 66 | |
| 2 | 2010 | 36 | |
| 3 | 2013 | 36 | |
| 4 | 2016 | 36 | |
| 5 | 2002 | 33 | |
| 6 | 2007 | 29 | |
| 7 | 2014 | 26 | |
| 8 | 2015 | 26 | |
| 9 | 2005 | 25 | |
| 10 | 2009 | 20 | |
| 11 | 2006 | 18 | |
| 12 | 2011 | 18 | |
| 13 | 2017 | 16 | |
| 14 | 2011 | 16 | |
| 15 | 2006 | 14 | |
| 16 | 2011 | 12 | |
| 17 | 2017 | 12 | |
| 18 | 2004 | 11 | |
| 19 | 2002 | 11 | |
| 20 | 2010 | 10 |
About I‐Jen Chiang
I‐Jen Chiang is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Molecular Biology and Signal Processing, having authored 51 papers that have together received 567 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (9 papers), Biomedical Text Mining and Ontologies (7 papers), Data Management and Algorithms (6 papers), Traumatic Brain Injury and Neurovascular Disturbances (5 papers), Rough Sets and Fuzzy Logic (5 papers), Topic Modeling (5 papers), Medical Image Segmentation Techniques (4 papers) and Medical Imaging and Analysis (4 papers). The work is most often cited by research in Neurology (59 citations), Health Informatics (8 citations), Neurology (80 citations), Computer Vision and Pattern Recognition (103 citations) and Health Information Management (21 citations). I‐Jen Chiang has collaborated with scholars based in Taiwan, United States and India. Frequent co-authors include Chun-Chih Liao, Furen Xiao, Jau‐Min Wong, Jane Yung-jen Hsu, Tsau Young Lin, Ajit Kumar, Thomas Mon-Hsian Hsieh, Yimin Liu, Yi‐Hsin Tsai and Chiehfeng Chen. Their work appears in journals such as Journal of Biomedical Informatics, Computers in Biology and Medicine, Applied Intelligence, Clinical Neurology and Neurosurgery and Human Pathology.
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.