Michelle Smerek

535 citations
13 papers · 345 · h-index 7

Impact in

Papers in

Michelle Smerek

12 papers receiving 341 citations

Peers

Michelle Smerek
Comparison fields: 5 of 72
  • Health Information Management 62
  • Computational Mathematics 2
  • Health Informatics 3
  • Geriatrics and Gerontology 4
  • General Health Professions 27
Replace Shelley A. Rusincovitch with:
Shelley A. Rusincovitch United States
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Amy Matcho United States
Fateme Moghbeli Iran
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Michelle Smerek relative to Shelley A. Rusincovitch United States Shelley A. Rusincovitch's profile →
Citations per field
00.5×1.5×
Shelley A. Rusincovitch · 1×
Citations per year

Countries citing papers authored by Michelle Smerek

Since Specialization
Citations

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

Fields of papers citing papers by Michelle Smerek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michelle Smerek. 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 Michelle Smerek. The network helps show where Michelle Smerek may publish in the future.

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2013150
2 201656
3 201637
4 201730
5 202030
6 202014
7 202112
8 20215
9
Can prospective usability evaluation predict data errors?
20105
10 20224
11 20211
12
Use of RxNorm and NDF-RT to normalize and characterize participant-reported medications in an i2b2-based research repository.
20141
13 20150

About Michelle Smerek

Michelle Smerek is a scholar working on Health Information Management, Surgery, Management Science and Operations Research, Molecular Biology and Artificial Intelligence, having authored 13 papers that have together received 345 indexed citations. Recurring topics across this work include Peripheral Artery Disease Management (4 papers), Electronic Health Records Systems (4 papers), Data Quality and Management (3 papers), Biomedical Text Mining and Ontologies (2 papers), Machine Learning in Healthcare (2 papers), Artificial Intelligence in Healthcare (1 paper), Health Systems, Economic Evaluations, Quality of Life (1 paper) and Aortic aneurysm repair treatments (1 paper). The work is most often cited by research in Health Information Management (62 citations), Computational Mathematics (2 citations), Health Informatics (3 citations), Geriatrics and Gerontology (4 citations) and General Health Professions (27 citations). Michelle Smerek has collaborated with scholars based in United States. Frequent co-authors include Rachel Richesson, Alan Bauck, W. Ed Hammond, Reesa Laws, Blake Cameron, Meredith Nahm, Robert M. Califf, Denise Cifelli, Gregory E. Simon and Shelley A. Rusincovitch. Their work appears in journals such as Journal of the American Medical Informatics Association, Clinical Trials, American Heart Journal, Journal of Vascular Surgery and Vascular Medicine.

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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