Eric LaRose
Impact in
- Health Informatics top 10%
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- Artificial Intelligence in Healthcare
Papers in
-
- Topic Modeling 2
- Advanced Text Analysis Techniques 1
- Machine Learning in Healthcare 1
- Machine Learning and Data Classification 1
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- Gene expression and cancer classification 1
- Co-authors
- Peggy Peissig (10 shared papers)Fereshteh S. Bashiri (4 shared papers)Ahmad P. Tafti (5 shared papers)John Mayer (3 shared papers)David Page (3 shared papers)Roshan M. D’Souza (1 shared paper)Zeyun Yu (1 shared paper)Robert M. Cronin (1 shared paper)
- Journals
- Journal of the American Medical Informatics Association (1 paper)Journal of Biomedical Informatics (1 paper)Data in Brief (1 paper)Methods of Information in Medicine (1 paper)Lecture notes in computer science (2 papers)
- Partner nations
- United States
In The Last Decade
Eric LaRose
10 papers receiving 266 citations
Peers
Comparison fields: 5 of 71
- Health Informatics 16
- Health Information Management 32
- Toxicology 12
- Computer Vision and Pattern Recognition 56
- Human-Computer Interaction 15
Countries citing papers authored by Eric LaRose
This map shows the geographic impact of Eric LaRose'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 Eric LaRose with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric LaRose more than expected).
Fields of papers citing papers by Eric LaRose
This network shows the impact of papers produced by Eric LaRose. 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 Eric LaRose. The network helps show where Eric LaRose may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric LaRose, 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 | 2016 | 71 | |
| 2 | 2018 | 37 | |
| 3 | 2017 | 37 | |
| 4 | 2018 | 37 | |
| 5 | 2019 | 31 | |
| 6 | 2018 | 24 | |
| 7 | 2017 | 18 | |
| 8 | 2017 | 15 | |
| 9 | Entity Matching Using Magellan: Matching Drug Reference Tables. | 2017 | 5 |
| 10 | 2022 | 2 |
About Eric LaRose
Eric LaRose is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 10 papers that have together received 277 indexed citations. Recurring topics across this work include Topic Modeling (2 papers), Advanced Neural Network Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Retinal Imaging and Analysis (1 paper), Gene expression and cancer classification (1 paper), Advanced Text Analysis Techniques (1 paper), Machine Learning in Healthcare (1 paper) and Machine Learning and Data Classification (1 paper). The work is most often cited by research in Health Informatics (16 citations), Health Information Management (32 citations), Toxicology (12 citations), Computer Vision and Pattern Recognition (56 citations) and Human-Computer Interaction (15 citations). Eric LaRose has collaborated with scholars based in United States. Frequent co-authors include Peggy Peissig, Fereshteh S. Bashiri, Ahmad P. Tafti, John Mayer, David Page, Roshan M. D’Souza, Zeyun Yu, Robert M. Cronin, Thomas A. Lasko and Huan Mo. Their work appears in journals such as Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, Data in Brief, Methods of Information in Medicine and Lecture notes in computer science.
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.