James Teo
Impact in
- Health Informatics top 0.5%
- Neurology top 1%
- Transcranial Magnetic Stimulation Studies
- Neurological disorders and treatments
- Botulinum Toxin and Related Neurological Disorders
- Long-Term Effects of COVID-19
- Vestibular and auditory disorders
Papers in ⓘ
- Neurology 22
- Transcranial Magnetic Stimulation Studies 18
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- Machine Learning in Healthcare 14
- Topic Modeling 9
- Co-authors
- John C. Rothwell (22 shared papers)Kailash P. Bhatia (11 shared papers)Mark J. Edwards (8 shared papers)Richard Dobson (24 shared papers)Orlando Swayne (5 shared papers)Daniel Bean (15 shared papers)Željko Kraljević (13 shared papers)Binith Cheeran (4 shared papers)
- Journals
- Clinical Neurophysiology (5 papers)PLoS ONE (4 papers)Movement Disorders (3 papers)Journal of Neurology Neurosurgery & Psychiatry (3 papers)npj Digital Medicine (3 papers)
- Partner nations
- United KingdomUnited StatesItaly
In The Last Decade
James Teo
87 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 130
- Health Informatics 160
- Neurology 800
- Neurology 779
- Rehabilitation 179
- Cognitive Neuroscience 477
Countries citing papers authored by James Teo
This map shows the geographic impact of James Teo'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 James Teo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Teo more than expected).
Fields of papers citing papers by James Teo
This network shows the impact of papers produced by James Teo. 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 James Teo. The network helps show where James Teo may publish in the future.
Co-authors
The 25 scholars most cited alongside James Teo, 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 94 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 183 | |
| 2 | 2020 | 152 | |
| 3 | 2020 | 127 | |
| 4 | 2020 | 127 | |
| 5 | 2008 | 100 | |
| 6 | 2023 | 99 | |
| 7 | 2012 | 94 | |
| 8 | 2013 | 89 | |
| 9 | 2007 | 81 | |
| 10 | 2017 | 77 | |
| 11 | 2010 | 68 | |
| 12 | 2011 | 66 | |
| 13 | 2009 | 55 | |
| 14 | 2011 | 53 | |
| 15 | 2011 | 47 | |
| 16 | 2007 | 47 | |
| 17 | 2016 | 46 | |
| 18 | 2008 | 44 | |
| 19 | 2017 | 43 | |
| 20 | 2024 | 43 |
About James Teo
James Teo is a scholar working on Neurology, Neurology, Artificial Intelligence, Epidemiology and Infectious Diseases, having authored 94 papers that have together received 2.4k indexed citations. Recurring topics across this work include Transcranial Magnetic Stimulation Studies (18 papers), COVID-19 Clinical Research Studies (14 papers), Machine Learning in Healthcare (14 papers), Muscle activation and electromyography studies (10 papers), Topic Modeling (9 papers), COVID-19 and healthcare impacts (8 papers), Sepsis Diagnosis and Treatment (8 papers) and Artificial Intelligence in Healthcare and Education (7 papers). The work is most often cited by research in Health Informatics (160 citations), Neurology (800 citations), Neurology (779 citations), Rehabilitation (179 citations) and Cognitive Neuroscience (477 citations). James Teo has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include John C. Rothwell, Kailash P. Bhatia, Mark J. Edwards, Richard Dobson, Orlando Swayne, Daniel Bean, Željko Kraljević, Binith Cheeran, Ajay M. Shah and Laura Avanzino. Their work appears in journals such as Clinical Neurophysiology, PLoS ONE, Movement Disorders, Journal of Neurology Neurosurgery & Psychiatry and npj Digital 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.