James Morrill
Impact in
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- Artificial Intelligence in Healthcare and Education
Papers in
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- Sepsis Diagnosis and Treatment 3
- Data-Driven Disease Surveillance 1
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- Machine Learning in Healthcare 3
- Co-authors
- Terry Lyons (5 shared papers)Sumanth Swaminathan (5 shared papers)Andrey Kormilitzin (2 shared papers)Alejo Nevado‐Holgado (2 shared papers)Patrick Kidger (1 shared paper)James Foster (2 shared papers)Sam Howison (1 shared paper)Ted Smith (2 shared papers)
- Journals
- Critical Care Medicine (1 paper)Journal of Cardiovascular Translational Research (1 paper)Scientific Reports (1 paper)Neural Information Processing Systems (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United KingdomUnited StatesFrance
In The Last Decade
James Morrill
8 papers receiving 57 citations
Peers
Comparison fields: 5 of 43
- Health Informatics 5
- Computational Mathematics 2
- Family Practice 3
- Health Information Management 4
- Statistical and Nonlinear Physics 10
Countries citing papers authored by James Morrill
This map shows the geographic impact of James Morrill'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 James Morrill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Morrill more than expected).
Fields of papers citing papers by James Morrill
This network shows the impact of papers produced by James Morrill. 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 James Morrill. The network helps show where James Morrill may publish in the future.
Co-authors
The 21 scholars most cited alongside James Morrill, 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 | 18 | |
| 2 | Neural Controlled Differential Equations for Irregular Time Series | 2020 | 14 |
| 3 | 2019 | 11 | |
| 4 | 2021 | 10 | |
| 5 | 2024 | 5 | |
| 6 | 2023 | 4 | |
| 7 | 2021 | 1 | |
| 8 | 2020 | 1 |
About James Morrill
James Morrill is a scholar working on Epidemiology, Artificial Intelligence, Signal Processing, Surgery and Cardiology and Cardiovascular Medicine, having authored 8 papers that have together received 64 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (3 papers), Sepsis Diagnosis and Treatment (3 papers), Time Series Analysis and Forecasting (2 papers), Artificial Intelligence in Healthcare (1 paper), Data-Driven Disease Surveillance (1 paper), Healthcare Technology and Patient Monitoring (1 paper), Clinical Reasoning and Diagnostic Skills (1 paper) and Music and Audio Processing (1 paper). The work is most often cited by research in Health Informatics (5 citations), Computational Mathematics (2 citations), Family Practice (3 citations), Health Information Management (4 citations) and Statistical and Nonlinear Physics (10 citations). James Morrill has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Terry Lyons, Sumanth Swaminathan, Andrey Kormilitzin, Alejo Nevado‐Holgado, Patrick Kidger, James Foster, Sam Howison, Ted Smith, Jacob P. Kelly and Marat Fudim. Their work appears in journals such as Critical Care Medicine, Journal of Cardiovascular Translational Research, Scientific Reports, Neural Information Processing Systems and arXiv (Cornell University).
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.