Kevin Lybarger

456 total citations
31 papers, 236 citations indexed

About

Kevin Lybarger is a scholar working on Artificial Intelligence, General Health Professions and Health Information Management. According to data from OpenAlex, Kevin Lybarger has authored 31 papers receiving a total of 236 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 7 papers in General Health Professions and 5 papers in Health Information Management. Recurrent topics in Kevin Lybarger's work include Machine Learning in Healthcare (9 papers), Topic Modeling (9 papers) and Biomedical Text Mining and Ontologies (4 papers). Kevin Lybarger is often cited by papers focused on Machine Learning in Healthcare (9 papers), Topic Modeling (9 papers) and Biomedical Text Mining and Ontologies (4 papers). Kevin Lybarger collaborates with scholars based in United States, United Kingdom and Norway. Kevin Lybarger's co-authors include Meliha Yetişgen, Mari Ostendorf, Özlem Uzuner, Thomas H. Payne, Andrew A. White, Trevor Cohen, Angad Singh, Dror Ben‐Zeev, Ross J. Lordon and Martin L. Gunn and has published in prestigious journals such as Journal of the American Medical Informatics Association, Psychiatric Services and BMJ Open.

In The Last Decade

Kevin Lybarger

26 papers receiving 231 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kevin Lybarger United States 9 101 64 42 39 36 31 236
Shan Chen United States 5 105 1.0× 34 0.5× 33 0.8× 23 0.6× 25 0.7× 9 231
Lina Sulieman United States 8 50 0.5× 76 1.2× 67 1.6× 21 0.5× 19 0.5× 18 255
Clive Stringer United Kingdom 5 83 0.8× 29 0.5× 40 1.0× 42 1.1× 68 1.9× 6 233
Douglas Conway United States 6 42 0.4× 74 1.2× 23 0.5× 46 1.2× 17 0.5× 11 226
Hannah Shucard United States 9 45 0.4× 161 2.5× 112 2.7× 30 0.8× 29 0.8× 22 364
Tiffany I. Leung United States 6 70 0.7× 69 1.1× 43 1.0× 11 0.3× 43 1.2× 25 251
Cláudia Maria Cabral Moro Brazil 8 144 1.4× 24 0.4× 34 0.8× 18 0.5× 80 2.2× 61 299
Betina Idnay United States 9 156 1.5× 42 0.7× 35 0.8× 8 0.2× 52 1.4× 23 327
Nan Kennedy United States 10 27 0.3× 28 0.4× 28 0.7× 8 0.2× 17 0.5× 20 177
Poonam Hosamani United States 7 163 1.6× 48 0.8× 28 0.7× 11 0.3× 45 1.3× 9 434

Countries citing papers authored by Kevin Lybarger

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Lybarger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin Lybarger

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Lybarger. A scholar is included among the top collaborators of Kevin Lybarger based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kevin Lybarger. Kevin Lybarger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lybarger, Kevin, Angad Singh, Brian R. Wood, et al.. (2025). Patient and clinician acceptability of automated extraction of social drivers of health from clinical notes in primary care. Journal of the American Medical Informatics Association. 32(5). 855–865.
2.
Lybarger, Kevin, Judy Y. Chen, Mahul Patel, et al.. (2025). Development and Evaluation of Machine Learning Models for the Identification of Surgical Site Infection in Electronic Health Records. Surgical Infections. 26(7). 474–481. 1 indexed citations
3.
Alemi, Farrokh, et al.. (2025). Artificial Intelligence for Management of Major Depression: Initial Design, Progress, and Research Plans. ALPHA PSYCHIATRY. 26(4). 44608–44608.
4.
Williams, Michelle S., et al.. (2024). Health text simplification: An annotated corpus for digestive cancer education and novel strategies for reinforcement learning. Journal of Biomedical Informatics. 158. 104727–104727. 3 indexed citations
5.
Halwani, Ahmad, Bridget T. McInnes, Fei Xia, et al.. (2024). CACER: Clinical concept Annotations for Cancer Events and Relations. Journal of the American Medical Informatics Association. 31(11). 2583–2594.
6.
Lybarger, Kevin, et al.. (2023). Extracting medication changes in clinical narratives using pre-trained language models. Journal of Biomedical Informatics. 139. 104302–104302. 8 indexed citations
7.
Crosslin, David R., Sean D. Mooney, Eric D. Morrell, et al.. (2023). Evaluating construct validity of computable acute respiratory distress syndrome definitions in adults hospitalized with COVID-19: an electronic health records based approach. BMC Pulmonary Medicine. 23(1). 292–292. 6 indexed citations
8.
Han, Bin, et al.. (2023). Prompt-based Extraction of Social Determinants of Health Using Few-shot Learning. 385–393. 9 indexed citations
9.
Kessler, Larry G., Margaret A. Au, Monica Zigman Suchsland, et al.. (2023). Symptoms and signs of lung cancer prior to diagnosis: case–control study using electronic health records from ambulatory care within a large US-based tertiary care centre. BMJ Open. 13(4). e068832–e068832. 8 indexed citations
10.
11.
Lybarger, Kevin, et al.. (2023). Leveraging natural language processing to augment structured social determinants of health data in the electronic health record. Journal of the American Medical Informatics Association. 30(8). 1389–1397. 19 indexed citations
12.
13.
Lybarger, Kevin, et al.. (2022). Event-Based Clinical Finding Extraction from Radiology Reports with Pre-trained Language Model. Journal of Digital Imaging. 36(1). 91–104. 6 indexed citations
14.
15.
Lybarger, Kevin, et al.. (2021). Identifying ARDS using the Hierarchical Attention Network with Sentence Objectives Framework.. PubMed. 2021. 823–832. 1 indexed citations
16.
Lybarger, Kevin, Mari Ostendorf, & Meliha Yetişgen. (2020). Annotating social determinants of health using active learning, and characterizing determinants using neural event extraction. Journal of Biomedical Informatics. 113. 103631–103631. 54 indexed citations
17.
Payne, Thomas H., et al.. (2018). Using voice to create inpatient progress notes: effects on note timeliness, quality, and physician satisfaction. JAMIA Open. 1(2). 218–226. 15 indexed citations
18.
Payne, Thomas H., et al.. (2017). Improving Electronic Inpatient Progress Notes Using Voice: Results from the VGEENS Project.. AMIA. 1 indexed citations
19.
20.
Malcolm, David J., et al.. (2011). Advances in Wind Turbine Site Assessment. 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. 1 indexed citations

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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