Thomas Falconer
Impact in
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- Artificial Intelligence in Healthcare and Education
- Health Information Management top 10%
- Electronic Health Records Systems
- Artificial Intelligence in Healthcare
Papers in
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- Liver Disease Diagnosis and Treatment 2
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- Statistical Methods in Clinical Trials 2
- Co-authors
- George Hripcsak (6 shared papers)Patrick Ryan (3 shared papers)Nigam H. Shah (2 shared papers)Borim Ryu (1 shared paper)Martin Seneviratne (1 shared paper)Mehr Kashyap (1 shared paper)Rae Woong Park (4 shared papers)Juan M. Banda (1 shared paper)
- Journals
- Journal of the American Medical Informatics Association (3 papers)Transfusion (1 paper)JCO Clinical Cancer Informatics (1 paper)Journal of Diabetes and its Complications (1 paper)Digestive Diseases (1 paper)
- Partner nations
- United StatesSouth KoreaGermany
In The Last Decade
Thomas Falconer
8 papers receiving 65 citations
Peers
Comparison fields: 5 of 50
- Health Informatics 9
- Health Information Management 20
- Artificial Intelligence 29
- Statistics and Probability 5
- Internal Medicine 2
Countries citing papers authored by Thomas Falconer
This map shows the geographic impact of Thomas Falconer'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 Thomas Falconer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Falconer more than expected).
Fields of papers citing papers by Thomas Falconer
This network shows the impact of papers produced by Thomas Falconer. 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 Thomas Falconer. The network helps show where Thomas Falconer may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Falconer, 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 | 22 | |
| 2 | 2020 | 20 | |
| 3 | 2020 | 15 | |
| 4 | 2023 | 3 | |
| 5 | 2024 | 3 | |
| 6 | 2023 | 2 | |
| 7 | 2024 | 1 | |
| 8 | 2023 | 1 | |
| 9 | 2025 | 0 | |
| 10 | 2024 | 0 | |
| 11 | 2025 | 0 |
About Thomas Falconer
Thomas Falconer is a scholar working on Epidemiology, Statistics and Probability, Molecular Biology, Pathology and Forensic Medicine and Cardiology and Cardiovascular Medicine, having authored 11 papers that have together received 67 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (2 papers), Liver Disease Diagnosis and Treatment (2 papers), Machine Learning in Healthcare (2 papers), Liver Disease and Transplantation (2 papers), Pharmacovigilance and Adverse Drug Reactions (1 paper), Diabetes Management and Research (1 paper), Metabolism, Diabetes, and Cancer (1 paper) and Advanced Statistical Process Monitoring (1 paper). The work is most often cited by research in Health Informatics (9 citations), Health Information Management (20 citations), Artificial Intelligence (29 citations), Statistics and Probability (5 citations) and Internal Medicine (2 citations). Thomas Falconer has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include George Hripcsak, Patrick Ryan, Nigam H. Shah, Borim Ryu, Martin Seneviratne, Mehr Kashyap, Rae Woong Park, Juan M. Banda, Sooyoung Yoo and Karthik Natarajan. Their work appears in journals such as Journal of the American Medical Informatics Association, Transfusion, JCO Clinical Cancer Informatics, Journal of Diabetes and its Complications and Digestive Diseases.
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.