Christopher Herrick
Impact in
- Health Information Management top 10%
- Artificial Intelligence in Healthcare
- Electronic Health Records Systems
Papers in
- Genetics 2
- Chronic Lymphocytic Leukemia Research 2
-
- Machine Learning in Healthcare 1
- Co-authors
- Shawn N. Murphy (9 shared papers)Kavishwar B. Wagholikar (3 shared papers)Víctor M. Castro (2 shared papers)Vivian S. Gainer (2 shared papers)Martin Rees (2 shared papers)Jeffrey G. Klann (1 shared paper)Taowei David Wang (1 shared paper)Christina Fischer (2 shared papers)
- Journals
- Journal of the American Medical Informatics Association (2 papers)Blood Advances (2 papers)Journal of Digital Imaging (1 paper)Journal of Biomedical Informatics (1 paper)Journal of Medical Systems (1 paper)
- Partner nations
- United StatesSouth Korea
In The Last Decade
Christopher Herrick
10 papers receiving 132 citations
Peers
Comparison fields: 5 of 53
- Health Information Management 17
- Health Informatics 5
- Genetics 9
- Biological Psychiatry 2
- Cardiology and Cardiovascular Medicine 16
Countries citing papers authored by Christopher Herrick
This map shows the geographic impact of Christopher Herrick'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 Christopher Herrick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Herrick more than expected).
Fields of papers citing papers by Christopher Herrick
This network shows the impact of papers produced by Christopher Herrick. 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 Christopher Herrick. The network helps show where Christopher Herrick may publish in the future.
Co-authors
The 25 scholars most cited alongside Christopher Herrick, 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 | 2021 | 34 | |
| 2 | 2014 | 23 | |
| 3 | 2018 | 21 | |
| 4 | 2018 | 19 | |
| 5 | 2014 | 19 | |
| 6 | 2024 | 9 | |
| 7 | 2019 | 4 | |
| 8 | 2025 | 2 | |
| 9 | Extending i2b2 into a framework for semantic abstraction of EHR to facilitate rapid development and portability of Health IT applications. | 2019 | 2 |
| 10 | 1973 | 1 |
About Christopher Herrick
Christopher Herrick is a scholar working on Genetics, Artificial Intelligence, Immunology, Infectious Diseases and Molecular Biology, having authored 10 papers that have together received 134 indexed citations. Recurring topics across this work include Immunodeficiency and Autoimmune Disorders (2 papers), Chronic Lymphocytic Leukemia Research (2 papers), Tuberculosis Research and Epidemiology (1 paper), Lymphoma Diagnosis and Treatment (1 paper), Diverse Musicological Studies (1 paper), Blood Pressure and Hypertension Studies (1 paper), Machine Learning in Healthcare (1 paper) and Radiology practices and education (1 paper). The work is most often cited by research in Health Information Management (17 citations), Health Informatics (5 citations), Genetics (9 citations), Biological Psychiatry (2 citations) and Cardiology and Cardiovascular Medicine (16 citations). Christopher Herrick has collaborated with scholars based in United States and South Korea. Frequent co-authors include Shawn N. Murphy, Kavishwar B. Wagholikar, Víctor M. Castro, Vivian S. Gainer, Martin Rees, Jeffrey G. Klann, Taowei David Wang, Christina Fischer, Calum A. MacRae and Bhaswati Ghosh. Their work appears in journals such as Journal of the American Medical Informatics Association, Blood Advances, Journal of Digital Imaging, Journal of Biomedical Informatics and Journal of Medical Systems.
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.