Michael G. Kahn

129 papers receiving 3.4k citations

Michael G. Kahn's Hit Papers

A Harmonized Data Quality Assessment Terminology and Framework for the Secondary Use of Electronic Health Record Data 2016 · 361 citations
3610+3+6Years since publication100200300

Peers

Michael G. Kahn
Comparison fields: 5 of 170
  • Health Information Management 540
  • Health Informatics 60
  • Applied Microbiology and Biotechnology 77
  • Management Science and Operations Research 339
  • Geriatrics and Gerontology 74
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Countries citing papers authored by Michael G. Kahn

Since Specialization
Citations

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

Fields of papers citing papers by Michael G. Kahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 134 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Harmonized Data Quality Assessment Terminology and Framework for the Secondary Use of Electronic Health Record Data
Hit paper breakdown →
2016361
2 2012195
3 2014148
4 2013108
5
Glutathione in calf trabecular meshwork and its relation to aqueous humor outflow facility.
1983102
6 201595
7 199187
8 201077
9 198976
10 202164
11 201461
12 201158
13
A randomized, prospective evaluation of an interventional program to discontinue intravenous antibiotics at two tertiary care teaching institutions.
199758
14 201755
15 199153
16 201353
17
An expert system for culture-based infection control surveillance.
199353
18 201352
19 199752
20 199750

About Michael G. Kahn

Michael G. Kahn is a scholar working on Health Information Management, Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications and Molecular Biology, having authored 134 papers that have together received 3.5k indexed citations. Recurring topics across this work include Electronic Health Records Systems (24 papers), Data Quality and Management (13 papers), Biomedical Text Mining and Ontologies (12 papers), Advanced Database Systems and Queries (9 papers), Semantic Web and Ontologies (7 papers), Machine Learning in Healthcare (6 papers), Health Systems, Economic Evaluations, Quality of Life (5 papers) and Scientific Computing and Data Management (5 papers). The work is most often cited by research in Health Information Management (540 citations), Health Informatics (60 citations), Applied Microbiology and Biotechnology (77 citations), Management Science and Operations Research (339 citations) and Geriatrics and Gerontology (74 citations). Michael G. Kahn has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Jeffrey S. Brown, Chunhua Weng, Daksha Ranade, Lisa M. Schilling, Steve Cousins, Toan C. Ong, Lawrence M. Fagan, Diane L. Fairclough, Marion R. Sills and John F. Steiner. Their work appears in journals such as Journal of the American Medical Informatics Association, International Journal of Radiation Oncology*Biology*Physics, Pediatric Diabetes, Medical Care and PLoS ONE.

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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