Anthony Shek

840 citations
15 papers · 306 · h-index 8

Impact in

Papers in

Anthony Shek

15 papers receiving 303 citations

Peers

Anthony Shek
Comparison fields: 5 of 61
  • Health Informatics 25
  • Infectious Diseases 137
  • Health Information Management 15
  • Neurology 45
  • Cardiology and Cardiovascular Medicine 28
Replace Syed Muhammad Ismail Shah with:
Syed Muhammad Ismail Shah Pakistan
Željko Kraljević United Kingdom
Patrick Botting United States
Antonella Rispoli Italy
Anna Ostropolets United States
Sandy Joung United States
Walaa Alsharif Saudi Arabia
Luca Mingardi United States
Ankit Bansal India
Sarah Denny United Kingdom
Anthony Shek relative to Syed Muhammad Ismail Shah Pakistan Syed Muhammad Ismail Shah's profile →
Citations per field
00.5×5.7×
Syed Muhammad Ismail Shah · 1×
Citations per year

Countries citing papers authored by Anthony Shek

Since Specialization
Citations

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

Fields of papers citing papers by Anthony Shek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anthony Shek. 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 Anthony Shek. The network helps show where Anthony Shek may publish in the future.

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2020152
2 202453
3 202220
4 202120
5 202114
6 201912
7 20248
8 20237
9 20217
10 19934
11 20213
12 20252
13 20232
14 20201
15 20241

About Anthony Shek

Anthony Shek is a scholar working on Artificial Intelligence, Infectious Diseases, Molecular Biology, Nephrology and Rehabilitation, having authored 15 papers that have together received 306 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (5 papers), COVID-19 Clinical Research Studies (4 papers), Topic Modeling (3 papers), Biomedical Text Mining and Ontologies (2 papers), Dementia and Cognitive Impairment Research (1 paper), Stroke Rehabilitation and Recovery (1 paper), Electronic Health Records Systems (1 paper) and Telemedicine and Telehealth Implementation (1 paper). The work is most often cited by research in Health Informatics (25 citations), Infectious Diseases (137 citations), Health Information Management (15 citations), Neurology (45 citations) and Cardiology and Cardiovascular Medicine (28 citations). Anthony Shek has collaborated with scholars based in United Kingdom, Germany and Hong Kong. Frequent co-authors include James Teo, Richard Dobson, Daniel Bean, Rebecca Bendayan, Željko Kraljević, Ajay M. Shah, Rosita Zakeri, Kevin O’Gallagher, Thomas Searle and Łukasz Roguski. Their work appears in journals such as Epilepsia, European Journal of Heart Failure, European Journal of Neurology, The Lancet Digital Health and BMC Medical Informatics and Decision Making.

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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