Michael Sharkey

612 total citations
28 papers, 324 citations indexed

About

Michael Sharkey is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Michael Sharkey has authored 28 papers receiving a total of 324 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Pulmonary and Respiratory Medicine, 7 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Michael Sharkey's work include Pulmonary Hypertension Research and Treatments (12 papers), Advanced X-ray and CT Imaging (5 papers) and Artificial Intelligence in Healthcare and Education (5 papers). Michael Sharkey is often cited by papers focused on Pulmonary Hypertension Research and Treatments (12 papers), Advanced X-ray and CT Imaging (5 papers) and Artificial Intelligence in Healthcare and Education (5 papers). Michael Sharkey collaborates with scholars based in United Kingdom, United States and Netherlands. Michael Sharkey's co-authors include Krit Dwivedi, Samer Alabed, Andrew J. Swift, David G. Kiely, Luis Filgueira, Graham R. Leggatt, Linda A. Dunn, Ian H. Frazer, Robert W. Tindle and Jian Zhou and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Radiology.

In The Last Decade

Michael Sharkey

24 papers receiving 308 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Sharkey United Kingdom 12 90 80 65 53 52 28 324
Ayumi Watanabe United States 11 55 0.6× 92 1.1× 40 0.6× 78 1.5× 7 0.1× 38 330
P Borkowski Poland 13 59 0.7× 96 1.2× 35 0.5× 13 0.2× 24 0.5× 27 411
Ryota Tanaka Japan 14 158 1.8× 144 1.8× 84 1.3× 29 0.5× 80 1.5× 46 479
John S. Butterfield United Kingdom 14 182 2.0× 30 0.4× 14 0.2× 16 0.3× 90 1.7× 27 551
Tiffany M. Yu United States 10 89 1.0× 127 1.6× 41 0.6× 20 0.4× 24 0.5× 25 414
Jibin Zhang China 10 34 0.4× 14 0.2× 125 1.9× 73 1.4× 24 0.5× 17 316
Federica Cappuccini United Kingdom 9 90 1.0× 18 0.2× 97 1.5× 109 2.1× 25 0.5× 15 363
Ari Pollack United States 6 10 0.1× 56 0.7× 48 0.7× 70 1.3× 380 7.3× 12 607

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-authorship network of co-authors of Michael Sharkey

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Sharkey. A scholar is included among the top collaborators of Michael Sharkey based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Sharkey. Michael Sharkey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Sharkey, Michael, Samer Alabed, Krit Dwivedi, et al.. (2025). CT scoring system to defined thrombus distribution in chronic thromboembolic pulmonary hypertension. British Journal of Radiology. 99(1177). 83–91.
2.
Sharkey, Michael, et al.. (2025). Addressing Bullying and Cyberbullying in Public Health: A Systematic Review of Interventions for Healthcare and Public Health Professionals. International Journal of Environmental Research and Public Health. 22(11). 1682–1682.
3.
Dwivedi, Krit, Michael Sharkey, Samer Alabed, et al.. (2024). Improving Prognostication in Pulmonary Hypertension Using AI-quantified Fibrosis and Radiologic Severity Scoring at Baseline CT. Radiology. 310(2). e231718–e231718. 12 indexed citations
4.
Alabed, Samer, Michael Sharkey, Krit Dwivedi, et al.. (2024). Artificial intelligence-based echocardiography assessment to detect pulmonary hypertension. ERJ Open Research. 11(3). 592–2024. 1 indexed citations
5.
Sharkey, Michael, et al.. (2024). Advancements in cardiac structures segmentation: a comprehensive systematic review of deep learning in CT imaging. Frontiers in Cardiovascular Medicine. 11. 1323461–1323461. 16 indexed citations
6.
Sharkey, Michael, Pankaj Garg, Smitha Rajaram, et al.. (2024). A systematic review of artificial intelligence tools for chronic pulmonary embolism on CT pulmonary angiography. SHILAP Revista de lepidopterología. 4. 1335349–1335349. 7 indexed citations
7.
Thomas, Richard, David Capener, Krit Dwivedi, et al.. (2024). Clinical assessment of an AI tool for measuring biventricular parameters on cardiac MR. Frontiers in Cardiovascular Medicine. 11. 1279298–1279298. 2 indexed citations
8.
Matthews, S., Jonathan Taylor, Michael Sharkey, et al.. (2023). Evaluating the performance of artificial intelligence software for lung nodule detection on chest radiographs in a retrospective real-world UK population. BMJ Open. 13(11). e077348–e077348. 11 indexed citations
9.
Dwivedi, Krit, et al.. (2023). External validation, radiological evaluation, and development of deep learning automatic lung segmentation in contrast-enhanced chest CT. European Radiology. 34(4). 2727–2737. 6 indexed citations
10.
Mamalakis, Michail, Krit Dwivedi, Michael Sharkey, et al.. (2023). A transparent artificial intelligence framework to assess lung disease in pulmonary hypertension. Scientific Reports. 13(1). 3812–3812. 12 indexed citations
12.
Alabed, Samer, Michael Sharkey, Michail Mamalakis, et al.. (2022). Quality of reporting in AI cardiac MRI segmentation studies – A systematic review and recommendations for future studies. Frontiers in Cardiovascular Medicine. 9. 956811–956811. 17 indexed citations
13.
Alabed, Samer, Asad Mahmood, Michael Sharkey, et al.. (2022). The quality of reporting in cardiac MRI artificial intelligence segmentation studies - a systematic review. European Heart Journal - Cardiovascular Imaging. 23(Supplement_2). 1 indexed citations
14.
Alabed, Samer, Krit Dwivedi, Yousef Shahin, et al.. (2022). Right ventricular remodelling in pulmonary arterial hypertension predicts treatment response. Heart. 108(17). 1392–1400. 19 indexed citations
15.
Sharkey, Michael, Jonathan Taylor, Samer Alabed, et al.. (2022). Fully automatic cardiac four chamber and great vessel segmentation on CT pulmonary angiography using deep learning. Frontiers in Cardiovascular Medicine. 9. 983859–983859. 17 indexed citations
16.
Sharkey, Michael, et al.. (2022). Fully automatic deep learning pulmonary hypertension diagnosis using CT pulmonary angiography. 3655–3655. 1 indexed citations
17.
Sharkey, Michael. (2001). Majority Does Not Rule: The Trouble with Majority-Rule Consensus Trees. Cladistics. 17(3). 282–284. 20 indexed citations
18.
Frazer, Ian H., Ranjeny Thomas, Jian Zhou, et al.. (1999). Potential strategies utilised by papillomavirus to evade host immunity. Immunological Reviews. 168(1). 131–142. 79 indexed citations
19.
Sharkey, Michael, W Grabski, Martha L. McCollough, & Timothy G. Berger. (1992). Postcoital appearance of a median raphe cyst. Journal of the American Academy of Dermatology. 26(2). 273–274. 8 indexed citations
20.
Sharkey, Michael. (1989). A Hypothesis‐Independent Method of Character Weighting for Cladistic Analysis. Cladistics. 5(1). 63–86. 43 indexed citations

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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