Robert Faist
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Epilepsy research and treatment
Papers in
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- Machine Learning in Healthcare 4
- Topic Modeling 3
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- Epilepsy research and treatment 3
- Co-authors
- John Pestian (5 shared papers)Tracy A. Glauser (5 shared papers)Hansel M. Greiner (3 shared papers)Francesco T. Mangano (3 shared papers)Katherine Holland‐Bouley (2 shared papers)Benjamin D. Wissel (2 shared papers)Shannon M. Standridge (2 shared papers)Brian Connolly (1 shared paper)
- Journals
- Epilepsia (1 paper)Epilepsy Research (1 paper)Acta Neurologica Scandinavica (1 paper)Journal of Medical Systems (1 paper)Visible Language (1 paper)
- Partner nations
- United States
In The Last Decade
Robert Faist
6 papers receiving 149 citations
Peers
Comparison fields: 5 of 50
- Health Informatics 41
- Psychiatry and Mental health 64
- Health Information Management 12
- Artificial Intelligence 60
- Cognitive Neuroscience 30
Countries citing papers authored by Robert Faist
This map shows the geographic impact of Robert Faist'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 Robert Faist with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Faist more than expected).
Fields of papers citing papers by Robert Faist
This network shows the impact of papers produced by Robert Faist. 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 Robert Faist. The network helps show where Robert Faist may publish in the future.
Co-authors
The 25 scholars most cited alongside Robert Faist, 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 | 59 | |
| 2 | 2019 | 45 | |
| 3 | 2017 | 21 | |
| 4 | 2019 | 18 | |
| 5 | 2014 | 6 | |
| 6 | A Statistical Approach for Visualizing the Quality of Multi-Hospital Data | 2014 | 2 |
About Robert Faist
Robert Faist is a scholar working on Artificial Intelligence, Psychiatry and Mental health, Molecular Biology, Pediatrics, Perinatology and Child Health and Health Information Management, having authored 6 papers that have together received 151 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (4 papers), Epilepsy research and treatment (3 papers), Topic Modeling (3 papers), Pharmaceutical Practices and Patient Outcomes (1 paper), Pharmacological Effects and Toxicity Studies (1 paper), Big Data Technologies and Applications (1 paper), Data Visualization and Analytics (1 paper) and Fetal and Pediatric Neurological Disorders (1 paper). The work is most often cited by research in Health Informatics (41 citations), Psychiatry and Mental health (64 citations), Health Information Management (12 citations), Artificial Intelligence (60 citations) and Cognitive Neuroscience (30 citations). Robert Faist has collaborated with scholars based in United States. Frequent co-authors include John Pestian, Tracy A. Glauser, Hansel M. Greiner, Francesco T. Mangano, Katherine Holland‐Bouley, Benjamin D. Wissel, Shannon M. Standridge, Brian Connolly, Ravindra Arya and Kevin Bretonnel Cohen. Their work appears in journals such as Epilepsia, Epilepsy Research, Acta Neurologica Scandinavica, Journal of Medical Systems and Visible Language.
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.