Eric S. Vorm
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Safety Research top 10%
- Ethics and Social Impacts of AI
Papers in
-
- Explainable Artificial Intelligence (XAI) 3
- AI-based Problem Solving and Planning 1
-
- Big Data and Business Intelligence 2
- Co-authors
- David J. Combs (1 shared paper)David Gunning (1 shared paper)Yunyan Wang (1 shared paper)Andrew Miller (2 shared papers)Anthony M. Harrison (1 shared paper)J. Gregory Trafton (1 shared paper)
- Journals
- IEEE Intelligent Systems (1 paper)International Journal of Human-Computer Interaction (1 paper)Military Medicine (1 paper)Publisher (1 paper)DOAJ (DOAJ: Directory of Open Access Journals) (1 paper)
- Partner nations
- United StatesAustralia
In The Last Decade
Eric S. Vorm
9 papers receiving 231 citations
Peers
Comparison fields: 5 of 89
- Health Informatics 49
- Safety Research 50
- Artificial Intelligence 130
- Information Systems and Management 23
- Computer Science Applications 10
Countries citing papers authored by Eric S. Vorm
This map shows the geographic impact of Eric S. Vorm'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 S. Vorm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric S. Vorm more than expected).
Fields of papers citing papers by Eric S. Vorm
This network shows the impact of papers produced by Eric S. Vorm. 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 S. Vorm. The network helps show where Eric S. Vorm may publish in the future.
Co-authors
The 6 scholars most cited alongside Eric S. Vorm, 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 | 2022 | 103 | |
| 2 | 2021 | 98 | |
| 3 | 2018 | 20 | |
| 4 | 2021 | 6 | |
| 5 | 2020 | 6 | |
| 6 | Assessing Demand for Transparency in Intelligent Systems Using Machine Learning | 2018 | 3 |
| 7 | Assessing the Value of Transparency in Recommender Systems: An End-User Perspective | 2018 | 2 |
| 8 | 2020 | 2 | |
| 9 | 2016 | 2 |
About Eric S. Vorm
Eric S. Vorm is a scholar working on Artificial Intelligence, Management Information Systems, Safety Research, Social Psychology and Clinical Psychology, having authored 9 papers that have together received 242 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (3 papers), Ethics and Social Impacts of AI (2 papers), Big Data and Business Intelligence (2 papers), Q Methodology Applications (1 paper), AI-based Problem Solving and Planning (1 paper), Resilience and Mental Health (1 paper), Suicide and Self-Harm Studies (1 paper) and Economic and Environmental Valuation (1 paper). The work is most often cited by research in Health Informatics (49 citations), Safety Research (50 citations), Artificial Intelligence (130 citations), Information Systems and Management (23 citations) and Computer Science Applications (10 citations). Eric S. Vorm has collaborated with scholars based in United States and Australia. Frequent co-authors include David J. Combs, David Gunning, Yunyan Wang, Andrew Miller, Anthony M. Harrison and J. Gregory Trafton. Their work appears in journals such as IEEE Intelligent Systems, International Journal of Human-Computer Interaction, Military Medicine, Publisher and DOAJ (DOAJ: Directory of Open Access Journals).
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.