André Carrington
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 10%
- Explainable Artificial Intelligence (XAI)
- Machine Learning in Healthcare
- Adversarial Robustness in Machine Learning
- AI in cancer detection
Papers in
-
- Anomaly Detection Techniques and Applications 1
- Machine Learning and Data Classification 1
- Adversarial Robustness in Machine Learning 1
- Surgery 1
- Co-authors
- Andreas Holzinger (2 shared papers)Heimo Müller (1 shared paper)Paul Fieguth (2 shared papers)Helen Chen (2 shared papers)Douglas G. Manuel (2 shared papers)Steven Hawken (2 shared papers)Darine El‐Chaâr (1 shared paper)Malia S. Q. Murphy (1 shared paper)
- Journals
- Canadian Journal of Emergency Medicine (1 paper)PLoS ONE (1 paper)BMC Medical Informatics and Decision Making (1 paper)Canadian Geriatrics Journal (1 paper)Multiple Sclerosis and Related Disorders (1 paper)
- Partner nations
- CanadaUnited StatesAustria
In The Last Decade
André Carrington
5 papers receiving 356 citations
Peers
Comparison fields: 5 of 102
- Health Informatics 91
- Artificial Intelligence 191
- Family Practice 8
- Health Information Management 20
- Safety Research 38
Countries citing papers authored by André Carrington
This map shows the geographic impact of André Carrington'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 André Carrington with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites André Carrington more than expected).
Fields of papers citing papers by André Carrington
This network shows the impact of papers produced by André Carrington. 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 André Carrington. The network helps show where André Carrington may publish in the future.
Co-authors
The 25 scholars most cited alongside André Carrington, 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 | 2020 | 226 | |
| 2 | 2020 | 120 | |
| 3 | 2022 | 16 | |
| 4 | 2014 | 2 | |
| 5 | 2023 | 1 | |
| 6 | 2025 | 0 | |
| 7 | 2025 | 0 | |
| 8 | 2020 | 0 | |
| 9 | 2023 | 0 |
About André Carrington
André Carrington is a scholar working on Artificial Intelligence, Surgery, Pathology and Forensic Medicine, Neurology and General Health Professions, having authored 9 papers that have together received 365 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (1 paper), Anomaly Detection Techniques and Applications (1 paper), Machine Learning and Data Classification (1 paper), Digital Imaging for Blood Diseases (1 paper), Clinical practice guidelines implementation (1 paper), Adversarial Robustness in Machine Learning (1 paper), Healthcare Systems and Practices (1 paper) and Multiple Sclerosis Research Studies (1 paper). The work is most often cited by research in Health Informatics (91 citations), Artificial Intelligence (191 citations), Family Practice (8 citations), Health Information Management (20 citations) and Safety Research (38 citations). André Carrington has collaborated with scholars based in Canada, United States and Austria. Frequent co-authors include Andreas Holzinger, Heimo Müller, Paul Fieguth, Helen Chen, Douglas G. Manuel, Steven Hawken, Darine El‐Chaâr, Malia S. Q. Murphy, Richard I. Aviv and Mark Walker. Their work appears in journals such as Canadian Journal of Emergency Medicine, PLoS ONE, BMC Medical Informatics and Decision Making, Canadian Geriatrics Journal and Multiple Sclerosis and Related Disorders.
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.