Frank Meng

405 total citations
29 papers, 212 citations indexed

About

Frank Meng is a scholar working on Artificial Intelligence, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Frank Meng has authored 29 papers receiving a total of 212 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 7 papers in Molecular Biology and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Frank Meng's work include Biomedical Text Mining and Ontologies (7 papers), Semantic Web and Ontologies (5 papers) and Topic Modeling (4 papers). Frank Meng is often cited by papers focused on Biomedical Text Mining and Ontologies (7 papers), Semantic Web and Ontologies (5 papers) and Topic Modeling (4 papers). Frank Meng collaborates with scholars based in United States, Australia and Germany. Frank Meng's co-authors include Wesley W. Chu, Craig A. Morioka, Ricky K. Taira, William Hsu, Hooshang Kangarloo, Alex Bui, Suzie El‐Saden, John W. Harmon, Shiwen Shen and Jean Garcia-Gathright and has published in prestigious journals such as Journal of Clinical Oncology, Clinical Pharmacology & Therapeutics and Drug and Alcohol Dependence.

In The Last Decade

Frank Meng

25 papers receiving 206 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Frank Meng United States 9 97 57 47 32 30 29 212
Mitra Montazeri Iran 7 115 1.2× 30 0.5× 56 1.2× 44 1.4× 28 0.9× 20 254
Ran Lee United States 8 149 1.5× 29 0.5× 23 0.5× 17 0.5× 45 1.5× 36 365
Mahdieh Montazeri Iran 7 106 1.1× 41 0.7× 81 1.7× 46 1.4× 13 0.4× 25 293
Jiye An China 11 80 0.8× 106 1.9× 69 1.5× 54 1.7× 49 1.6× 30 423
Kevin Faust Canada 8 172 1.8× 32 0.6× 164 3.5× 37 1.2× 50 1.7× 12 380
Paul C. Pearlman United States 8 50 0.5× 42 0.7× 61 1.3× 33 1.0× 20 0.7× 21 310
Braden Soper United States 6 164 1.7× 18 0.3× 27 0.6× 16 0.5× 32 1.1× 16 284
Rahul Thapa United States 10 162 1.7× 25 0.4× 52 1.1× 30 0.9× 11 0.4× 15 354
Jimison Iavindrasana Switzerland 10 108 1.1× 12 0.2× 49 1.0× 40 1.3× 66 2.2× 18 312

Countries citing papers authored by Frank Meng

Since Specialization
Citations

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

Fields of papers citing papers by Frank Meng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frank Meng

This figure shows the co-authorship network connecting the top 25 collaborators of Frank Meng. A scholar is included among the top collaborators of Frank Meng 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 Frank Meng. Frank Meng 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.
Fonda, Jennifer R., Anne N. Banducci, Victoria Ameral, et al.. (2025). Sex and race-ethnicity influences on opioid overdose deaths among veterans diagnosed with opioid use disorder between 2016 and 2021. Drug and Alcohol Dependence. 274. 112764–112764.
2.
Livingston, Nicholas A., Anne N. Banducci, Michael Davenport, et al.. (2025). Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.. Journal of Psychopathology and Clinical Science. 134(4). 448–457.
3.
Livingston, Nicholas A., Michael Davenport, Rachel Mosher Henke, et al.. (2022). The impact of COVID-19 and rapid policy exemptions expanding on access to medication for opioid use disorder (MOUD): A nationwide Veterans Health Administration cohort study. Drug and Alcohol Dependence. 241. 109678–109678. 13 indexed citations
4.
Dhond, Rupali P., Sarah Leatherman, Frank Meng, et al.. (2021). Rapid implementation of a modular clinical trial informatics solution for COVID-19 research. Informatics in Medicine Unlocked. 27. 100788–100788.
5.
Fillmore, Nathanael R., Chris Meyer, Daniel Chen, et al.. (2020). The Veterans Affairs Precision Oncology Data Repository, a Clinical, Genomic, and Imaging Research Database. Patterns. 1(6). 100083–100083. 5 indexed citations
6.
Do, Nhan, Robert L. Grossman, Nathanael R. Fillmore, et al.. (2019). The Veterans Precision Oncology Data Commons: Transforming VA data into a national resource for research in precision oncology. Seminars in Oncology. 46(4-5). 314–320. 8 indexed citations
7.
Fillmore, Nathanael R., David Cheng, David Tuck, et al.. (2019). A predictive model for survival in non-small cell lung cancer (NSCLC) based on electronic health record (EHR) and tumor sequencing data at the Department of Veterans Affairs (VA).. Journal of Clinical Oncology. 37(15_suppl). 109–109. 1 indexed citations
8.
Lee, Jerry, Kathleen M. Darcy, Hai Hu, et al.. (2019). From Discovery to Practice and Survivorship: Building a National Real‐World Data Learning Healthcare Framework for Military and Veteran Cancer Patients. Clinical Pharmacology & Therapeutics. 106(1). 52–57. 17 indexed citations
9.
Meng, Frank, et al.. (2018). Enhance wound healing monitoring through a thermal imaging based smartphone app. 60–60. 11 indexed citations
10.
Meng, Frank, et al.. (2018). An innovative app for the management of chronic wound treatment. 3–4. 3 indexed citations
11.
Shen, Shiwen, Simon Han, Robert E. Weiss, et al.. (2016). A Bayesian model for estimating multi-state disease progression. Computers in Biology and Medicine. 81. 111–120. 10 indexed citations
12.
Morioka, Craig A., Frank Meng, Ricky K. Taira, et al.. (2016). Automatic Classification of Ultrasound Screening Examinations of the Abdominal Aorta. Journal of Digital Imaging. 29(6). 742–748. 17 indexed citations
13.
Brennan, Caitlin W., et al.. (2016). Feasibility of Automating Patient Acuity Measurement Using a Machine Learning Algorithm. Journal of Nursing Measurement. 24(3). 419–427. 1 indexed citations
14.
Shen, Shiwen, et al.. (2015). A Continuous Markov Model Approach Using Individual Patient Data to Estimate Mean Sojourn Time of Lung Cancer.. AMIA. 1 indexed citations
15.
Meng, Frank & Craig A. Morioka. (2015). Automating the generation of lexical patterns for processing free text in clinical documents. Journal of the American Medical Informatics Association. 22(5). 980–986. 5 indexed citations
16.
Garcia-Gathright, Jean, Frank Meng, & William Hsu. (2014). UCLA at TREC 2014 Clinical Decision Support Track: Exploring Language Models, Query Expansion, and Boosting. Text REtrieval Conference. 7 indexed citations
17.
Morioka, Craig A., Suzie El‐Saden, Whitney B. Pope, et al.. (2008). A methodology to integrate clinical data for the efficient assessment of brain-tumor patients. Informatics for Health and Social Care. 33(1). 55–68. 2 indexed citations
18.
Meng, Frank, Ricky K. Taira, Alex Bui, Hooshang Kangarloo, & Bernard M. Churchill. (2005). Automatic generation of repeated patient information for tailoring clinical notes. International Journal of Medical Informatics. 74(7-8). 663–673. 5 indexed citations
19.
Meng, Frank, et al.. (2004). Information Extraction Using Semantic Patterns for Populating Clinical Data Models.. 10–16. 3 indexed citations
20.
Meng, Frank. (1999). A natural language interface for information retrieval from forms on the World Wide Web. International Conference on Information Systems. 540–545. 5 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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