Peter J. Haug

160 papers receiving 4.2k citations

Peers

Peter J. Haug
Comparison fields: 5 of 164
  • Health Information Management 830
  • Health Informatics 89
  • Family Practice 81
  • Artificial Intelligence 1.2k
  • Issues, ethics and legal aspects 42
Replace Nicolette F. de Keizer with:
Nicolette F. de Keizer Netherlands
Ling Li China
William Hersh United States
G. Octo Barnett United States
E. Andrew Balas United States
Harold P. Lehmann United States
Ameen Abu–Hanna Netherlands
Robert A. Greenes United States
Christian Lovis Switzerland
Niels Peek United Kingdom
Peter J. Haug relative to Nicolette F. de Keizer Netherlands Nicolette F. de Keizer's profile →
Citations per field
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Nicolette F. de Keizer · 1×
Citations per year

Countries citing papers authored by Peter J. Haug

Since Specialization
Citations

This map shows the geographic impact of Peter J. Haug'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 Peter J. Haug with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter J. Haug more than expected).

Fields of papers citing papers by Peter J. Haug

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter J. Haug. 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 Peter J. Haug. The network helps show where Peter J. Haug may publish in the future.

Co-authors

The 25 scholars most cited alongside Peter J. Haug, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Peter J. Haug Line = papers co-authored together Peter J. Haug links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 166 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007200
2 2000200
3 2008193
4 2009171
5 2005161
6 2005151
7 2012144
8 2008112
9 2004109
10 2007102
11 200387
12 200583
13 200178
14 199078
15 201575
16 200269
17
The Arden Syntax for Medical Logic Modules.
199066
18
Experience with a mixed semantic/syntactic parser.
199562
19 200759
20 200857

About Peter J. Haug

Peter J. Haug is a scholar working on Health Information Management, Artificial Intelligence, Molecular Biology, Epidemiology and General Health Professions, having authored 166 papers that have together received 4.5k indexed citations. Recurring topics across this work include Electronic Health Records Systems (38 papers), Biomedical Text Mining and Ontologies (38 papers), Topic Modeling (14 papers), Machine Learning in Healthcare (13 papers), Semantic Web and Ontologies (12 papers), Bayesian Modeling and Causal Inference (10 papers), Radiology practices and education (9 papers) and Health Sciences Research and Education (8 papers). The work is most often cited by research in Health Information Management (830 citations), Health Informatics (89 citations), Family Practice (81 citations), Artificial Intelligence (1.2k citations) and Issues, ethics and legal aspects (42 citations). Peter J. Haug has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Dominik Aronsky, Wendy W. Chapman, R. Scott Evans, Marcelo Fiszman, Stanley M. Huff, Nathan C. Dean, Lee M. Christensen, Lisa Cannon‐Albright, Marc S. Williams and Spencer S. Jones. Their work appears in journals such as Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, International Journal of Medical Informatics, Artificial Intelligence in Medicine and Medical Decision Making.

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.

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