James Geller
Impact in
- Artificial Intelligence top 2%
- Semantic Web and Ontologies
- Sentiment Analysis and Opinion Mining
- Topic Modeling
- Molecular Biology top 5%
- Biomedical Text Mining and Ontologies
Papers in
-
- Semantic Web and Ontologies 45
- Sentiment Analysis and Opinion Mining 11
- Logic, Reasoning, and Knowledge 9
-
- Biomedical Text Mining and Ontologies 106
- Co-authors
- Yehoshua Perl (107 shared papers)Michael H Halper (53 shared papers)Soon Ae Chun (49 shared papers)Xiang Ji (8 shared papers)Christopher Ochs (25 shared papers)Huanying Gu (19 shared papers)Gai Elhanan (22 shared papers)Zhe He (15 shared papers)
- Journals
- Journal of Biomedical Informatics (22 papers)Journal of the American Medical Informatics Association (8 papers)Artificial Intelligence in Medicine (5 papers)BMC Medical Informatics and Decision Making (4 papers)Data & Knowledge Engineering (3 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
James Geller
212 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 94
- Artificial Intelligence 716
- Molecular Biology 1.1k
- Health Information Management 127
- Software 71
- Health Informatics 29
Countries citing papers authored by James Geller
This map shows the geographic impact of James Geller'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 James Geller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Geller more than expected).
Fields of papers citing papers by James Geller
This network shows the impact of papers produced by James Geller. 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 James Geller. The network helps show where James Geller may publish in the future.
Co-authors
The 25 scholars most cited alongside James Geller, 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 221 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 112 | |
| 2 | 2006 | 77 | |
| 3 | 2013 | 69 | |
| 4 | 2014 | 45 | |
| 5 | 2011 | 37 | |
| 6 | 1991 | 36 | |
| 7 | 2003 | 34 | |
| 8 | 2009 | 34 | |
| 9 | Auditing the UMLS for redundant classifications. | 2002 | 33 |
| 10 | 2014 | 33 | |
| 11 | 2002 | 32 | |
| 12 | 2017 | 29 | |
| 13 | 2008 | 28 | |
| 14 | 1999 | 27 | |
| 15 | 1999 | 27 | |
| 16 | 2015 | 26 | |
| 17 | 2016 | 26 | |
| 18 | 2017 | 26 | |
| 19 | 1998 | 25 | |
| 20 | 2007 | 25 |
About James Geller
James Geller is a scholar working on Artificial Intelligence, Molecular Biology, Computer Networks and Communications, Information Systems and Health Information Management, having authored 221 papers that have together received 2.3k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (106 papers), Semantic Web and Ontologies (45 papers), Advanced Database Systems and Queries (25 papers), Sentiment Analysis and Opinion Mining (11 papers), Logic, Reasoning, and Knowledge (9 papers), Information Retrieval and Search Behavior (7 papers), Artificial Intelligence in Healthcare (7 papers) and Model-Driven Software Engineering Techniques (7 papers). The work is most often cited by research in Artificial Intelligence (716 citations), Molecular Biology (1.1k citations), Health Information Management (127 citations), Software (71 citations) and Health Informatics (29 citations). James Geller has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Yehoshua Perl, Michael H Halper, Soon Ae Chun, Xiang Ji, Christopher Ochs, Huanying Gu, Gai Elhanan, Zhe He, Yugyung Lee and Zhi Wei. Their work appears in journals such as Journal of Biomedical Informatics, Journal of the American Medical Informatics Association, Artificial Intelligence in Medicine, BMC Medical Informatics and Decision Making and Data & Knowledge Engineering.
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.