Eric V. Strobl
Impact in
- Statistics and Probability top 10%
- Statistical Methods and Inference
Papers in
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- Machine Learning in Healthcare 4
- Bayesian Modeling and Causal Inference 2
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- Statistical Methods and Inference 3
- Co-authors
- Shyam Visweswaran (2 shared papers)Thomas A. Lasko (4 shared papers)Robert Elliott (1 shared paper)Toshihiro Okubo (1 shared paper)Matt Cole (1 shared paper)Katherine P. Rankin (2 shared papers)Peter Spirtes (1 shared paper)Luisito Bertinelli (1 shared paper)
- Journals
- Computers in Biology and Medicine (1 paper)Biological Psychiatry (1 paper)npj Digital Medicine (1 paper)Early Intervention in Psychiatry (1 paper)Journal of Affective Disorders (1 paper)
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Eric V. Strobl
14 papers receiving 231 citations
Peers
Comparison fields: 5 of 89
- Health Informatics 5
- Statistics and Probability 27
- Developmental Neuroscience 12
- Artificial Intelligence 75
- Psychiatry and Mental health 35
Countries citing papers authored by Eric V. Strobl
This map shows the geographic impact of Eric V. Strobl'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 V. Strobl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric V. Strobl more than expected).
Fields of papers citing papers by Eric V. Strobl
This network shows the impact of papers produced by Eric V. Strobl. 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 V. Strobl. The network helps show where Eric V. Strobl may publish in the future.
Co-authors
The 23 scholars most cited alongside Eric V. Strobl, 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 | 2019 | 77 | |
| 2 | 2017 | 33 | |
| 3 | 2015 | 32 | |
| 4 | 2012 | 19 | |
| 5 | 2012 | 18 | |
| 6 | 2018 | 16 | |
| 7 | 2023 | 14 | |
| 8 | 2023 | 7 | |
| 9 | 2022 | 7 | |
| 10 | 2024 | 4 | |
| 11 | 2024 | 3 | |
| 12 | 2024 | 3 | |
| 13 | 2024 | 2 | |
| 14 | 2025 | 1 |
About Eric V. Strobl
Eric V. Strobl is a scholar working on Artificial Intelligence, Statistics and Probability, Cognitive Neuroscience, Genetics and Economics and Econometrics, having authored 14 papers that have together received 236 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (4 papers), Statistical Methods and Inference (3 papers), Schizophrenia research and treatment (2 papers), Genetic Associations and Epidemiology (2 papers), Bayesian Modeling and Causal Inference (2 papers), Advanced Neuroimaging Techniques and Applications (1 paper), Nerve injury and regeneration (1 paper) and Alzheimer's disease research and treatments (1 paper). The work is most often cited by research in Health Informatics (5 citations), Statistics and Probability (27 citations), Developmental Neuroscience (12 citations), Artificial Intelligence (75 citations) and Psychiatry and Mental health (35 citations). Eric V. Strobl has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Shyam Visweswaran, Thomas A. Lasko, Robert Elliott, Toshihiro Okubo, Matt Cole, Katherine P. Rankin, Peter Spirtes, Luisito Bertinelli, Bruce L. Miller and Shaun M. Eack. Their work appears in journals such as Computers in Biology and Medicine, Biological Psychiatry, npj Digital Medicine, Early Intervention in Psychiatry and Journal of Affective Disorders.
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.