Luke V. Rasmussen

6.8k total citations
83 papers, 2.1k citations indexed

About

Luke V. Rasmussen is a scholar working on Molecular Biology, Artificial Intelligence and Health Information Management. According to data from OpenAlex, Luke V. Rasmussen has authored 83 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Molecular Biology, 25 papers in Artificial Intelligence and 24 papers in Health Information Management. Recurrent topics in Luke V. Rasmussen's work include Biomedical Text Mining and Ontologies (39 papers), Electronic Health Records Systems (21 papers) and Machine Learning in Healthcare (18 papers). Luke V. Rasmussen is often cited by papers focused on Biomedical Text Mining and Ontologies (39 papers), Electronic Health Records Systems (21 papers) and Machine Learning in Healthcare (18 papers). Luke V. Rasmussen collaborates with scholars based in United States, Philippines and United Kingdom. Luke V. Rasmussen's co-authors include Peggy Peissig, Jennifer A. Pacheco, Jyotishman Pathak, Joshua C. Denny, Abel Kho, Justin Starren, Christopher G. Chute, Iftikhar J. Kullo, Richard L. Berg and Katherine M. Newton and has published in prestigious journals such as Nucleic Acids Research, Journal of Clinical Investigation and SHILAP Revista de lepidopterología.

In The Last Decade

Luke V. Rasmussen

78 papers receiving 2.0k citations

Peers

Countries citing papers authored by Luke V. Rasmussen

Since Specialization

Citations

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

Fields of papers citing papers by Luke V. Rasmussen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luke V. Rasmussen. 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 Luke V. Rasmussen. The network helps show where Luke V. Rasmussen may publish in the future.

Co-authorship network of co-authors of Luke V. Rasmussen

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Novel enzyme-based reduced representation method for DNA methylation profiling with low inputs 2025 ·Nucleic Acids Research ·(unknown), Kathryn A. Helmin, (unknown), (unknown), Manuel A. Torres Acosta, (unknown), Anthony M. Joudi, Nurbek Mambetsariev, Luisa Morales‐Nebreda, Mengjia Kang, Luke V. Rasmussen, (unknown), Hiam Abdala‐Valencia, Benjamin D. Singer	0
2	Results of the ACCOuNT Trial: A Multi‐Institutional Prospective Pharmacogenomics Implementation Trial for African American Inpatients 2025 ·Clinical Pharmacology & Therapeutics ·(unknown), Kevin J. O’Leary, Edith A. Nutescu, (unknown), Tai C. Chen, Gregory W. Ruhnke, James C. Lee, David L. George, Larry House, Randall W. Knoebel, Luke V. Rasmussen, (unknown), (unknown), Kiang-Teck J Yeo, Minoli A. Perera, Mark J. Ratain, David Meltzer, Peter H. O’Donnell	1
3	Addressing barriers in FAIR data practices for biomedical data 2023 ·Scientific Data ·Laura D. Hughes, Ginger Tsueng, Jack DiGiovanna, Thomas D. Horvath, Luke V. Rasmussen, Tor Savidge, Thomas Stoeger, Serdar Turkarslan, Qinglong Wu, Chunlei Wu, Andrew I. Su, Lars Pache, (unknown)	22
4	Machine learning links unresolving secondary pneumonia to mortality in patients with severe pneumonia, including COVID-19 2023 ·Journal of Clinical Investigation ·Catherine A. Gao, Nikolay S. Markov, Thomas Stoeger, Anna Pawlowski, Mengjia Kang, Prasanth Nannapaneni, Rogan A. Grant, Chiagozie I. Pickens, James M. Walter, Jacqueline M. Kruser, Luke V. Rasmussen, Daniel Schneider, Justin Starren, Helen K. Donnelly, Alvaro Donayre, Yuan Luo, G. R. Scott Budinger, Richard G. Wunderink, Alexander V. Misharin, Benjamin D. Singer	23
5	Comparing the effects of four common drug classes on the progression of mild cognitive impairment to dementia using electronic health records 2023 ·Scientific Reports ·Jie Xu, Fei Wang, Chengxi Zang, Hao Zhang, (unknown), Ava L. Liberman, Cynthia M. Stonnington, Makoto Ishii, Prakash Adekkanattu, (unknown), Chengsheng Mao, Luke V. Rasmussen, Zhenxing Xu, (unknown), Jennifer A. Pacheco, Yifan Peng, Guoqian Jiang, Richard Isaacson, Jyotishman Pathak	4
6	AD-BERT: Using pre-trained language model to predict the progression from mild cognitive impairment to Alzheimer's disease 2023 ·Journal of Biomedical Informatics ·Chengsheng Mao, Jie Xu, Luke V. Rasmussen, Yikuan Li, Prakash Adekkanattu, Jennifer A. Pacheco, Borna Bonakdarpour, Robert Vassar, Shen Li, (unknown), Fei Wang, Jyotishman Pathak, Yuan Luo	29
7	ReviewR: a light-weight and extensible tool for manual review of clinical records 2022 ·JAMIA Open ·David Mayer, Luke V. Rasmussen, Christopher Roark, Michael G. Kahn, Lisa M. Schilling, Laura K. Wiley	3
8	Desiderata for the development of next-generation electronic health record phenotype libraries 2021 ·GigaScience ·Martin Chapman, Shahzad Mumtaz, Luke V. Rasmussen, Andreas Karwath, Georgios V. Gkoutos, Chuang Gao, Daniel Thayer, Jennifer A. Pacheco, Helen Parkinson, Rachel Richesson, Emily Jefferson, Spiros Denaxas, Vasa Ćurčin	16
9	Identifying sub-phenotypes of acute kidney injury using structured and unstructured electronic health record data with memory networks 2020 ·Journal of Biomedical Informatics ·Zhenxing Xu, (unknown), (unknown), Yuan Luo, Tamara Isakova, Prakash Adekkanattu, Jessica S. Ancker, Guoqian Jiang, Richard C. Kiefer, Jennifer A. Pacheco, Luke V. Rasmussen, Jyotishman Pathak, Fei Wang	51
10	Participant choices for return of genomic results in the eMERGE Network 2020 ·Genetics in Medicine ·Christin Hoell, Julia Wynn, Luke V. Rasmussen, Keith Marsolo, Sharon Aufox, Wendy K. Chung, John J. Connolly, Robert R. Freimuth, (unknown), Håkon Håkonarson, Margaret Harr, Ingrid A. Holm, Iftikhar J. Kullo, Philip E. Lammers, Kathleen A. Leppig, Nancy D. Leslie, Melanie F. Myers, Richard R. Sharp, Maureen E. Smith, Cynthia A. Prows	24
11	Developing a FHIR-based EHR phenotyping framework: A case study for identification of patients with obesity and multiple comorbidities from discharge summaries 2019 ·Journal of Biomedical Informatics ·Na Hong, Andrew Wen, (unknown), (unknown), Paul Kingsbury, Luke V. Rasmussen, Jennifer A. Pacheco, Prakash Adekkanattu, Fei Wang, Yuan Luo, Jyotishman Pathak, Hongfang Liu, (unknown)	41
12	Stratified Mortality Prediction of Patients with Acute Kidney Injury in Critical Care 2019 ·Studies in health technology and informatics ·Zhenxing Xu, Yuan Luo, Prakash Adekkanattu, Jessica S. Ancker, Guoqian Jiang, Richard C. Kiefer, Jennifer A. Pacheco, Luke V. Rasmussen, Jyotishman Pathak, Fei Wang	12
13	Genomic Information for Clinicians in the Electronic Health Record: Lessons Learned From the Clinical Genome Resource Project and the Electronic Medical Records and Genomics Network 2019 ·Frontiers in Genetics ·Marc S. Williams, Casey Overby Taylor, Nephi Walton, (unknown), Samuel Aronson, Robert R. Freimuth, Luke V. Rasmussen, Eric S. Hall, Cynthia A. Prows, Wendy K. Chung, Alexander Fedotov, Jordan G. Nestor, Chunhua Weng, Robb Rowley, Georgia L. Wiesner, Gail P. Jarvik, Guilherme Del Fiol	33
14	Prototype Development: Context-Driven Dynamic XML Ophthalmologic Data Capture Application 2017 ·JMIR Medical Informatics ·Peggy Peissig, (unknown), (unknown), (unknown), (unknown), Catherine A. McCarty, (unknown), (unknown), Jennifer A. Pacheco, Jyotishman Pathak, Stephen B. Ellis, Joshua C. Denny, Luke V. Rasmussen, Gerard Tromp, Marc S. Williams, Tamara R. Vrabec, Murray H. Brilliant	2
15	Practical considerations for implementing genomic information resources 2016 ·Applied Clinical Informatics ·Casey Lynnette Overby, John J. Connolly, Christopher G. Chute, Joshua C. Denny, Robert R. Freimuth, Andrea L. Hartzler, Ingrid A. Holm, Shannon Manzi, Jyotishman Pathak, Peggy Peissig, Maureen E. Smith, Marc S. Williams, Brian H. Shirts, Elena M. Stoffel, Peter Tarczy‐Hornoch, Carolyn R. Rohrer Vitek, Wendy A. Wolf, Justin Starren, Luke V. Rasmussen	22
16	Implementing Pharmacogenomic Clinical Decision Support: Design and Prescriber Response in the eMERGE Network. 2016 ·AMIA ·Timothy M. Herr, Josh F. Peterson, Luke V. Rasmussen, Pedro J. Caraballo	2
17	Evaluation of Existing Phenotype Authoring Tools for Clinical Research. 2014 ·AMIA ·Luke V. Rasmussen, Jie Xu, (unknown), (unknown), Jennifer A. Pacheco, Jyotishman Pathak, William K. Thompson, Joshua C. Denny, Huan Mo, Richard C. Kiefer, Peter Speltz, Enid Montague	1
18	Practical challenges in integrating genomic data into the electronic health record 2013 ·Genetics in Medicine ·Abel Kho, Luke V. Rasmussen, John J. Connolly, Peggy Peissig, Justin Starren, Håkon Håkonarson, M. Geoffrey Hayes	69
19	Rethinking the "Honest Broker" in the Changing Face of Security and Privacy. 2012 ·AMIA ·Luke V. Rasmussen, (unknown), Andrew D. Boyd, Bradley Malin, Shawn N. Murphy	1
20	Cataract research using electronic health records 2011 ·BMC Ophthalmology ·Carol Waudby, Richard L. Berg, James G. Linneman, Luke V. Rasmussen, Peggy Peissig, (unknown), Catherine A. McCarty	30

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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