Lee M. Christensen

867 total citations
18 papers, 564 citations indexed

About

Lee M. Christensen is a scholar working on Molecular Biology, Artificial Intelligence and Epidemiology. According to data from OpenAlex, Lee M. Christensen has authored 18 papers receiving a total of 564 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 11 papers in Artificial Intelligence and 5 papers in Epidemiology. Recurrent topics in Lee M. Christensen's work include Biomedical Text Mining and Ontologies (11 papers), Topic Modeling (10 papers) and Natural Language Processing Techniques (6 papers). Lee M. Christensen is often cited by papers focused on Biomedical Text Mining and Ontologies (11 papers), Topic Modeling (10 papers) and Natural Language Processing Techniques (6 papers). Lee M. Christensen collaborates with scholars based in United States, Australia and Sweden. Lee M. Christensen's co-authors include Peter J. Haug, Wendy W. Chapman, Marcelo Fiszman, Brett R. South, Noémie Elhadad, Sameer Pradhan, Hanna Suominen, David Martínez, Robert Olszewski and О. А. Иванов and has published in prestigious journals such as Journal of the American Medical Informatics Association, BMC Health Services Research and Journal of Biomedical Informatics.

In The Last Decade

Lee M. Christensen

18 papers receiving 530 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lee M. Christensen United States	11	377	324	96	83	59	18	564
Guy Divita United States	16	406 1.1×	409 1.3×	70 0.7×	132 1.6×	155 2.6×	54	748
Peter J. Embí United States	8	226 0.6×	181 0.6×	54 0.6×	189 2.3×	54 0.9×	13	574
Lyudmila Shagina United States	9	483 1.3×	534 1.6×	67 0.7×	200 2.4×	35 0.6×	12	793
Haijun Zhai United States	11	201 0.5×	120 0.4×	51 0.5×	82 1.0×	22 0.4×	19	464
Jungwei Fan United States	11	288 0.8×	249 0.8×	35 0.4×	82 1.0×	52 0.9×	51	533
Meliha Yetişgen United States	13	348 0.9×	206 0.6×	50 0.5×	119 1.4×	85 1.4×	53	641
Kory Kreimeyer United States	9	244 0.6×	174 0.5×	37 0.4×	81 1.0×	26 0.4×	16	570
Jessica Gronsbell Canada	11	149 0.4×	102 0.3×	45 0.5×	57 0.7×	60 1.0×	25	423
Susan H. Fenton United States	12	138 0.4×	157 0.5×	55 0.6×	227 2.7×	103 1.7×	62	502
Evan Sholle United States	15	135 0.4×	56 0.2×	85 0.9×	105 1.3×	74 1.3×	40	543

Countries citing papers authored by Lee M. Christensen

Since Specialization

Citations

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

Fields of papers citing papers by Lee M. Christensen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lee M. Christensen. 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 Lee M. Christensen. The network helps show where Lee M. Christensen may publish in the future.

Co-authorship network of co-authors of Lee M. Christensen

This figure shows the co-authorship network connecting the top 25 collaborators of Lee M. Christensen. A scholar is included among the top collaborators of Lee M. Christensen 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 Lee M. Christensen. Lee M. Christensen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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18 of 18 papers shown

Christensen, Lee M., et al.. (2024). Automatic Extraction of Skin and Soft Tissue Infection Status from Clinical Notes. Studies in health technology and informatics. 310. 579–583. 1 indexed citations

Panahi, Samin, Jamie N. Mayo, Eamonn Kennedy, et al.. (2024). Identifying clinical phenotypes of frontotemporal dementia in post-9/11 era veterans using natural language processing. Frontiers in Neurology. 15. 1270688–1270688. 3 indexed citations

Wray, Charlie M., Marzieh Vali, Louise C. Walter, et al.. (2021). Examining the association of social risk with heart failure readmission in the Veterans Health Administration. BMC Health Services Research. 21(1). 874–874. 8 indexed citations

Reeves, Ruth, Lee M. Christensen, Jeremiah R. Brown, et al.. (2021). Adaptation of an NLP system to a new healthcare environment to identify social determinants of health. Journal of Biomedical Informatics. 120. 103851–103851. 27 indexed citations

Conway, Mike, Salomeh Keyhani, Lee M. Christensen, et al.. (2019). Moonstone: a novel natural language processing system for inferring social risk from clinical narratives. Journal of Biomedical Semantics. 10(1). 6–6. 47 indexed citations

Reeves, Ruth, Brett R. South, Glenn T. Gobbel, et al.. (2018). Annotating Social Determinants of Health and Functional Status Information Using Publicly Accessible Corpora.. AMIA. 1 indexed citations

Mowery, Danielle L., Brett R. South, Lee M. Christensen, et al.. (2016). Normalizing acronyms and abbreviations to aid patient understanding of clinical texts: ShARe/CLEF eHealth Challenge 2013, Task 2. Journal of Biomedical Semantics. 7(1). 43–43. 19 indexed citations

Velupillai, Sumithra, Danielle L. Mowery, Samir Abdelrahman, Lee M. Christensen, & Wendy W. Chapman. (2015). BluLab: Temporal Information Extraction for the 2015 Clinical TempEval Challenge. 815–819. 19 indexed citations

Velupillai, Sumithra, Danielle L. Mowery, Samir Abdelrahman, Lee M. Christensen, & Wendy W. Chapman. (2015). Towards a Generalizable Time Expression Model for Temporal Reasoning in Clinical Notes.. PubMed. 2015. 1252–9. 4 indexed citations

10.

Pradhan, Sameer, Noémie Elhadad, Brett R. South, et al.. (2014). Evaluating the state of the art in disorder recognition and normalization of the clinical narrative. Journal of the American Medical Informatics Association. 22(1). 143–154. 105 indexed citations

11.

Dublin, Sascha, Rod Walker, Lee M. Christensen, et al.. (2013). Natural Language Processing to identify pneumonia from radiology reports. Pharmacoepidemiology and Drug Safety. 22(8). 834–841. 51 indexed citations

12.

Pradhan, Sameer, Noémie Elhadad, Brett R. South, et al.. (2013). Task 1: ShARe/CLEF eHealth evaluation lab 2013. 1179. 27 indexed citations

13.

Harkema, Henk, et al.. (2009). Methodology to develop and evaluate a semantic representation for NLP.. D-Scholarship@Pitt (University of Pittsburgh). 9 indexed citations

14.

Christensen, Lee M., et al.. (2009). ONYX. 19–19. 14 indexed citations

15.

Day, Suzanne, et al.. (2007). Identification of Trauma Patients at a Level 1 Trauma Center Utilizing Natural Language Processing. Journal of Trauma Nursing. 14(2). 79–83. 10 indexed citations

16.

Chapman, Wendy W., Lee M. Christensen, Michael M. Wagner, et al.. (2004). Classifying free-text triage chief complaints into syndromic categories with natural language processing. Artificial Intelligence in Medicine. 33(1). 31–40. 108 indexed citations

17.

Christensen, Lee M., Peter J. Haug, & Marcelo Fiszman. (2002). MPLUS. 3. 29–36. 69 indexed citations

18.

Haug, Peter J., et al.. (1997). A natural language parsing system for encoding admitting diagnoses.. PubMed. 814–8. 42 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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