Jeremy Irvin
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Health Informatics top 1%
- Epidemiology
- Internal Medicine top 5%
- Co-authors
- Pranav RajpurkarAndrew Y. NgMatthew P. LungrenBhavik N. PatelCurtis P. LanglotzChris ChuteSanjay BasuDomenico Mastrodicasa
- Topics
- COVID-19 diagnosis using AI (3 papers)Language and cultural evolution (2 papers)Artificial Intelligence in Healthcare and Education (2 papers)
- Journals
- Nature CommunicationsAmerican Journal of Respiratory and Critical Care MedicineScientific Reports
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Jeremy Irvin
16 papers receiving 490 citations
Peers
Comparison fields: 5 of 124
- Radiology, Nuclear Medicine and Imaging 132
- Artificial Intelligence 109
- Health Informatics 91
- Epidemiology 75
- Internal Medicine 67
Countries citing papers authored by Jeremy Irvin
This map shows the geographic impact of Jeremy Irvin'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 Jeremy Irvin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeremy Irvin more than expected).
Fields of papers citing papers by Jeremy Irvin
This network shows the impact of papers produced by Jeremy Irvin. 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 Jeremy Irvin. The network helps show where Jeremy Irvin may publish in the future.
Co-authorship network of co-authors of Jeremy Irvin
This figure shows the co-authorship network connecting the top 25 collaborators of Jeremy Irvin. A scholar is included among the top collaborators of Jeremy Irvin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jeremy Irvin. Jeremy Irvin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | Probabilistic Prediction of Laboratory Test Information Yield. | 0 |
| 6 | 12 | |
| 7 | 21 | |
| 8 | 9 | |
| 9 | 103 | |
| 10 | 37 | |
| 11 | 56 | |
| 12 | 80 | |
| 13 | 140 | |
| 14 | 1 | |
| 15 | 9 | |
| 16 | Dynamical systems modeling of the child-mother dyad: Causality between child-directed language complexity and language development. | 3 |
| 17 | 0 | |
| 18 | A survey of attitudes toward responsible pet ownership. | 23 |
About Jeremy Irvin
Jeremy Irvin is a scholar working on Health Informatics, Internal Medicine and Cultural Studies, having authored 18 papers that have together received 504 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (3 papers), Language and cultural evolution (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). The work is most often cited by research in Health Informatics (91 citations), Internal Medicine (67 citations) and Radiology, Nuclear Medicine and Imaging (132 citations). Jeremy Irvin has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Pranav Rajpurkar, Andrew Y. Ng, Matthew P. Lungren, Bhavik N. Patel, Curtis P. Langlotz, Chris Chute, Sanjay Basu, Domenico Mastrodicasa, Michael Bereket and Timothy J. Amrhein. Their work appears in journals such as Nature Communications, American Journal of Respiratory and Critical Care Medicine and Scientific Reports.
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.