Michel Gingras
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
Papers in
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- Lung Cancer Diagnosis and Treatment 2
- Cerebrovascular and Carotid Artery Diseases 1
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- Cardiac Valve Diseases and Treatments 1
- Pericarditis and Cardiac Tamponade 1
- Co-authors
- Sergio Pasian (2 shared papers)Daria Manos (2 shared papers)Jean M. Seely (2 shared papers)Stephen Lam (2 shared papers)Ming‐Sound Tsao (2 shared papers)Paul Burrowes (2 shared papers)Sukhinder Atkar-Khattra (2 shared papers)John R. Mayo (2 shared papers)
- Journals
- Canadian Journal of Anesthesia/Journal canadien d anesthésie (1 paper)The Annals of Thoracic Surgery (1 paper)Canadian Journal of Cardiology (1 paper)Journal of Thoracic Oncology (1 paper)The Lancet Digital Health (1 paper)
- Partner nations
- CanadaUnited StatesNetherlands
In The Last Decade
Michel Gingras
6 papers receiving 139 citations
Peers
Comparison fields: 5 of 34
- Health Informatics 16
- Radiology, Nuclear Medicine and Imaging 66
- Pulmonary and Respiratory Medicine 73
- Artificial Intelligence 19
- Cardiology and Cardiovascular Medicine 11
Countries citing papers authored by Michel Gingras
This map shows the geographic impact of Michel Gingras'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 Michel Gingras with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michel Gingras more than expected).
Fields of papers citing papers by Michel Gingras
This network shows the impact of papers produced by Michel Gingras. 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 Michel Gingras. The network helps show where Michel Gingras may publish in the future.
Co-authors
The 25 scholars most cited alongside Michel Gingras, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 90 | |
| 2 | 2016 | 33 | |
| 3 | 2019 | 7 | |
| 4 | 2021 | 7 | |
| 5 | 2012 | 4 | |
| 6 | 2019 | 2 |
About Michel Gingras
Michel Gingras is a scholar working on Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine, Epidemiology, Radiology, Nuclear Medicine and Imaging and Archeology, having authored 6 papers that have together received 143 indexed citations. Recurring topics across this work include Infective Endocarditis Diagnosis and Management (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Cerebrovascular and Carotid Artery Diseases (1 paper), Cardiac Imaging and Diagnostics (1 paper), Cardiac Valve Diseases and Treatments (1 paper), Paleopathology and ancient diseases (1 paper) and Pericarditis and Cardiac Tamponade (1 paper). The work is most often cited by research in Health Informatics (16 citations), Radiology, Nuclear Medicine and Imaging (66 citations), Pulmonary and Respiratory Medicine (73 citations), Artificial Intelligence (19 citations) and Cardiology and Cardiovascular Medicine (11 citations). Michel Gingras has collaborated with scholars based in Canada, United States and Netherlands. Frequent co-authors include Sergio Pasian, Daria Manos, Jean M. Seely, Stephen Lam, Ming‐Sound Tsao, Paul Burrowes, Sukhinder Atkar-Khattra, John R. Mayo, Lori Stewart and Scott Tsai. Their work appears in journals such as Canadian Journal of Anesthesia/Journal canadien d anesthésie, The Annals of Thoracic Surgery, Canadian Journal of Cardiology, Journal of Thoracic Oncology and The Lancet Digital Health.
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.