Michael H Halper

81 papers receiving 1.1k citations

Peers

Michael H Halper
Comparison fields: 5 of 51
  • Molecular Biology 844
  • Software 47
  • Health Information Management 56
  • Artificial Intelligence 193
  • Issues, ethics and legal aspects 12
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Citations per year

Countries citing papers authored by Michael H Halper

Since Specialization
Citations

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

Fields of papers citing papers by Michael H Halper

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael H Halper. 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 Michael H Halper. The network helps show where Michael H Halper may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael H Halper, 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 Michael H Halper Line = papers co-authored together Michael H Halper links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 83 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200680
2 200677
3 201144
4
Analysis of error concentrations in SNOMED.
200739
5 200334
6 200934
7
Auditing the UMLS for redundant classifications.
200233
8 200232
9 200828
10 201328
11 199927
12 199927
13 199825
14 200224
15 201524
16
Scalability of abstraction-network-based quality assurance to large SNOMED hierarchies.
201322
17 199921
18 200821
19 200920
20
A family-based framework for supporting quality assurance of biomedical ontologies in BioPortal.
201320

About Michael H Halper

Michael H Halper is a scholar working on Molecular Biology, Artificial Intelligence, Computer Networks and Communications, Software and Computer Science Applications, having authored 83 papers that have together received 1.1k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (64 papers), Semantic Web and Ontologies (17 papers), Advanced Database Systems and Queries (10 papers), Model-Driven Software Engineering Techniques (4 papers), Teaching and Learning Programming (3 papers), Electronic Health Records Systems (2 papers), Information Systems Education and Curriculum Development (2 papers) and Usability and User Interface Design (1 paper). The work is most often cited by research in Molecular Biology (844 citations), Software (47 citations), Health Information Management (56 citations), Artificial Intelligence (193 citations) and Issues, ethics and legal aspects (12 citations). Michael H Halper has collaborated with scholars based in United States, United Kingdom and Taiwan. Frequent co-authors include Yehoshua Perl, James Geller, Huanying Gu, Hua Min, Gai Elhanan, Yue Wang, Kent A. Spackman, C. Paul Morrey, James J. Cimino and George M. Hripcsak. Their work appears in journals such as Journal of Biomedical Informatics, Artificial Intelligence in Medicine, Journal of the American Medical Informatics Association, Methods of Information in Medicine 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.

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