Carsten Eickhoff
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
-
- Mobile Crowdsensing and Crowdsourcing
Papers in
-
- Topic Modeling 34
- Natural Language Processing Techniques 18
- Machine Learning in Healthcare 14
- Data Stream Mining Techniques 8
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- Information Retrieval and Search Behavior 19
- Co-authors
- Arjen P. de Vries (21 shared papers)Thomas Hofmann (5 shared papers)Ritambhara Singh (6 shared papers)Volkmar Falk (5 shared papers)Alexander Meyer (5 shared papers)Christopher G. Harris (2 shared papers)Padmini Srinivasan (2 shared papers)Boris Pfahringer (2 shared papers)
- Journals
- Scientific Reports (2 papers)ACM Transactions on Information Systems (2 papers)JMIR Medical Education (2 papers)Information Retrieval (2 papers)Journal of Medical Internet Research (2 papers)
- Partner nations
- United StatesSwitzerlandNetherlands
In The Last Decade
Carsten Eickhoff
105 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 138
- Health Informatics 182
- Computer Science Applications 348
- Artificial Intelligence 710
- Information Systems 361
- Health Information Management 66
Countries citing papers authored by Carsten Eickhoff
This map shows the geographic impact of Carsten Eickhoff'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 Carsten Eickhoff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carsten Eickhoff more than expected).
Fields of papers citing papers by Carsten Eickhoff
This network shows the impact of papers produced by Carsten Eickhoff. 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 Carsten Eickhoff. The network helps show where Carsten Eickhoff may publish in the future.
Co-authors
The 25 scholars most cited alongside Carsten Eickhoff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 117 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 225 | |
| 2 | 2012 | 126 | |
| 3 | 2012 | 112 | |
| 4 | 2014 | 100 | |
| 5 | 2018 | 90 | |
| 6 | 2020 | 88 | |
| 7 | 2016 | 77 | |
| 8 | 2022 | 74 | |
| 9 | 2021 | 73 | |
| 10 | 2011 | 64 | |
| 11 | 2020 | 55 | |
| 12 | 2020 | 53 | |
| 13 | How Crowdsourcable is Your Task | 2011 | 50 |
| 14 | 2023 | 35 | |
| 15 | 2024 | 34 | |
| 16 | 2015 | 31 | |
| 17 | 2011 | 24 | |
| 18 | 2018 | 22 | |
| 19 | 2013 | 19 | |
| 20 | 2017 | 19 |
About Carsten Eickhoff
Carsten Eickhoff is a scholar working on Artificial Intelligence, Information Systems, Molecular Biology, Computer Science Applications and Radiology, Nuclear Medicine and Imaging, having authored 117 papers that have together received 1.8k indexed citations. Recurring topics across this work include Topic Modeling (34 papers), Information Retrieval and Search Behavior (19 papers), Natural Language Processing Techniques (18 papers), Machine Learning in Healthcare (14 papers), Mobile Crowdsensing and Crowdsourcing (11 papers), Biomedical Text Mining and Ontologies (10 papers), Data Stream Mining Techniques (8 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). The work is most often cited by research in Health Informatics (182 citations), Computer Science Applications (348 citations), Artificial Intelligence (710 citations), Information Systems (361 citations) and Health Information Management (66 citations). Carsten Eickhoff has collaborated with scholars based in United States, Switzerland and Netherlands. Frequent co-authors include Arjen P. de Vries, Thomas Hofmann, Ritambhara Singh, Volkmar Falk, Alexander Meyer, Christopher G. Harris, Padmini Srinivasan, Boris Pfahringer, Christof Stamm and Jörg Kempfert. Their work appears in journals such as Scientific Reports, ACM Transactions on Information Systems, JMIR Medical Education, Information Retrieval and Journal of Medical Internet Research.
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.