Jacob Calvert
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Family Practice top 1%
- Clinical Reasoning and Diagnostic Skills
Papers in
- Epidemiology 15
- Sepsis Diagnosis and Treatment 12
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- Machine Learning in Healthcare 5
- Co-authors
- Ritankar Das (38 shared papers)Jana Hoffman (32 shared papers)Uli K. Chettipally (10 shared papers)Melissa Jay (8 shared papers)Qingqing Mao (24 shared papers)Christopher Barton (7 shared papers)Lisa Shieh (3 shared papers)Thomas Desautels (6 shared papers)
- Journals
- Computers in Biology and Medicine (4 papers)Frontiers in Pediatrics (2 papers)BMJ Open (2 papers)Clinical Therapeutics (2 papers)Nucleic Acids Research (2 papers)
- Partner nations
- United StatesUnited KingdomBelgium
In The Last Decade
Jacob Calvert
54 papers receiving 2.1k citations
Jacob Calvert's Hit Papers
Peers
Comparison fields: 5 of 136
- Health Informatics 180
- Family Practice 109
- Health Information Management 185
- Epidemiology 880
- Artificial Intelligence 648
Countries citing papers authored by Jacob Calvert
This map shows the geographic impact of Jacob Calvert'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 Jacob Calvert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacob Calvert more than expected).
Fields of papers citing papers by Jacob Calvert
This network shows the impact of papers produced by Jacob Calvert. 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 Jacob Calvert. The network helps show where Jacob Calvert may publish in the future.
Co-authors
The 25 scholars most cited alongside Jacob Calvert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach Hit paper breakdown → | 2016 | 362 |
| 2 | 2018 | 247 | |
| 3 | 2016 | 193 | |
| 4 | 2019 | 129 | |
| 5 | 2018 | 110 | |
| 6 | 2020 | 103 | |
| 7 | 2017 | 87 | |
| 8 | 2019 | 86 | |
| 9 | 2015 | 76 | |
| 10 | 2020 | 61 | |
| 11 | 2014 | 58 | |
| 12 | 2016 | 54 | |
| 13 | 2021 | 46 | |
| 14 | 2016 | 43 | |
| 15 | 2021 | 42 | |
| 16 | 2017 | 41 | |
| 17 | 2021 | 35 | |
| 18 | 2020 | 35 | |
| 19 | 2021 | 29 | |
| 20 | 2019 | 27 |
About Jacob Calvert
Jacob Calvert is a scholar working on Epidemiology, Artificial Intelligence, Cardiology and Cardiovascular Medicine, Infectious Diseases and Internal Medicine, having authored 57 papers that have together received 2.2k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (12 papers), Machine Learning in Healthcare (5 papers), Venous Thromboembolism Diagnosis and Management (4 papers), COVID-19 Clinical Research Studies (3 papers), COVID-19 diagnosis using AI (3 papers), RNA Interference and Gene Delivery (2 papers), Stochastic processes and statistical mechanics (2 papers) and Geophysical Methods and Applications (2 papers). The work is most often cited by research in Health Informatics (180 citations), Family Practice (109 citations), Health Information Management (185 citations), Epidemiology (880 citations) and Artificial Intelligence (648 citations). Jacob Calvert has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Ritankar Das, Jana Hoffman, Uli K. Chettipally, Melissa Jay, Qingqing Mao, Christopher Barton, Lisa Shieh, Thomas Desautels, Yaniv Kerem and Mitchell D. Feldman. Their work appears in journals such as Computers in Biology and Medicine, Frontiers in Pediatrics, BMJ Open, Clinical Therapeutics and Nucleic Acids Research.
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.