Michael Sharkey

652 citations
29 papers · 347 · h-index 12

Impact in

Papers in

Michael Sharkey

24 papers receiving 328 citations

Peers

Michael Sharkey
Comparison fields: 5 of 66
  • Health Informatics 19
  • Internal Medicine 14
  • Paleontology 31
  • Pulmonary and Respiratory Medicine 86
  • Critical Care and Intensive Care Medicine 11
Replace D.J. Connolly with:
D.J. Connolly United Kingdom
John S. Butterfield United Kingdom
Itay Maza Israel
Steven L. Maki United States
Ari Pollack United States
Tadashi Ozawa Japan
Djamshid Shirazian United States
Unity Jeffery United States
Jacqueline M. Gertz United States
Elena E. Gorbunova United States
Michael Sharkey relative to D.J. Connolly United Kingdom D.J. Connolly's profile →
Citations per field
00.5×7.8×
D.J. Connolly · 1×
Citations per year

Countries citing papers authored by Michael Sharkey

Since Specialization
Citations

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

Fields of papers citing papers by Michael Sharkey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199982
2 198946
3 202124
4 200120
5 202219
6 202219
7 202418
8 202217
9 199214
10 202313
11 202413
12 202311
13 202210
14 199210
15 20248
16 20237
17 20245
18 20243
19 20243
20 20211

About Michael Sharkey

Michael Sharkey is a scholar working on Pulmonary and Respiratory Medicine, Internal Medicine, Health Informatics, Genetics and Epidemiology, having authored 29 papers that have together received 347 indexed citations. Recurring topics across this work include Pulmonary Hypertension Research and Treatments (9 papers), Venous Thromboembolism Diagnosis and Management (3 papers), Artificial Intelligence in Healthcare and Education (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Advanced X-ray and CT Imaging (2 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers), Artificial Intelligence in Healthcare (1 paper) and Urologic and reproductive health conditions (1 paper). The work is most often cited by research in Health Informatics (19 citations), Internal Medicine (14 citations), Paleontology (31 citations), Pulmonary and Respiratory Medicine (86 citations) and Critical Care and Intensive Care Medicine (11 citations). Michael Sharkey has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Andrew J. Swift, Krit Dwivedi, Samer Alabed, David G. Kiely, Ian H. Frazer, Linda A. Dunn, Nigel A.J. McMillan, Jian Zhou, Ranjeny Thomas and Robert W. Tindle. Their work appears in journals such as Frontiers in Cardiovascular Medicine, British Journal of Radiology, ERJ Open Research, Cladistics and Heart.

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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