Todd Lingren

29 papers receiving 1.2k citations

Peers

Todd Lingren
Comparison fields: 5 of 120
  • Health Informatics 44
  • Health Information Management 143
  • Toxicology 35
  • Artificial Intelligence 283
  • Geriatrics and Gerontology 26
Replace Imre Solti with:
Imre Solti United States
Henry Lowe United States
Emmanuel Chazard France
Keith Marsolo United States
H. R. Warner United States
Henry C. Chueh United States
Rachel Richesson United States
Werner O. Hackl Austria
Kavishwar B. Wagholikar United States
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Todd Lingren relative to Imre Solti United States Imre Solti's profile →
Citations per field
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Citations per year

Countries citing papers authored by Todd Lingren

Since Specialization
Citations

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

Fields of papers citing papers by Todd Lingren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016245
2 201590
3 201787
4 201478
5 201466
6 201465
7 201260
8 201359
9
Building gold standard corpora for medical natural language processing tasks.
201255
10 201352
11 201443
12 201339
13 201338
14 202031
15 201528
16 201527
17 201326
18 201725
19 201423
20 201218

About Todd Lingren

Todd Lingren is a scholar working on Health Information Management, Artificial Intelligence, Molecular Biology, Epidemiology and Emergency Medical Services, having authored 29 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Electronic Health Records Systems (3 papers), Patient Safety and Medication Errors (2 papers), Biomedical Text Mining and Ontologies (2 papers), Natural Language Processing Techniques (2 papers), Pharmaceutical Practices and Patient Outcomes (1 paper), Obesity, Physical Activity, Diet (1 paper) and Data-Driven Disease Surveillance (1 paper). The work is most often cited by research in Health Informatics (44 citations), Health Information Management (143 citations), Toxicology (35 citations), Artificial Intelligence (283 citations) and Geriatrics and Gerontology (26 citations). Todd Lingren has collaborated with scholars based in United States and Hong Kong. Frequent co-authors include Imre Solti, Megan Kaiser, Qi Li, Haijun Zhai, Yizhao Ni, Louise Deléger, Laura Stoutenborough, John B. Harley, Eric S. Kirkendall and Keith Marsolo. Their work appears in journals such as Journal of the American Medical Informatics Association, BMC Medical Informatics and Decision Making, Journal of Medical Internet Research, Journal of Biomedical Informatics and Frontiers in Genetics.

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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