Son Doan

1.7k total citations
34 papers, 1.0k citations indexed

About

Son Doan is a scholar working on Artificial Intelligence, Molecular Biology and Epidemiology. According to data from OpenAlex, Son Doan has authored 34 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 20 papers in Molecular Biology and 8 papers in Epidemiology. Recurrent topics in Son Doan's work include Biomedical Text Mining and Ontologies (20 papers), Topic Modeling (13 papers) and Advanced Text Analysis Techniques (9 papers). Son Doan is often cited by papers focused on Biomedical Text Mining and Ontologies (20 papers), Topic Modeling (13 papers) and Advanced Text Analysis Techniques (9 papers). Son Doan collaborates with scholars based in United States, Japan and Vietnam. Son Doan's co-authors include Joshua C. Denny, Lemuel R. Waitman, Shane P. Stenner, K. Brandon Johnson, Hanzhang Xu, Nigel Collier, Mike Conway, Hua Xu, Ai Kawazoe and Hung Q. Ngo and has published in prestigious journals such as Bioinformatics, Journal of the American Medical Informatics Association and Academic Emergency Medicine.

In The Last Decade

Son Doan

33 papers receiving 974 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Son Doan United States 13 484 476 202 127 93 34 1.0k
Juan M. Banda United States 18 568 1.2× 296 0.6× 140 0.7× 193 1.5× 137 1.5× 62 1.5k
Jingcheng Du United States 19 729 1.5× 414 0.9× 169 0.8× 158 1.2× 70 0.8× 63 1.5k
Todd Lingren United States 19 415 0.9× 393 0.8× 132 0.7× 239 1.9× 48 0.5× 29 1.2k
Majid Rastegar-Mojarad United States 18 899 1.9× 796 1.7× 61 0.3× 164 1.3× 65 0.7× 48 1.5k
Siddhartha Jonnalagadda United States 22 868 1.8× 644 1.4× 52 0.3× 164 1.3× 48 0.5× 51 1.5k
Imre Solti United States 20 734 1.5× 676 1.4× 88 0.4× 224 1.8× 69 0.7× 35 1.4k
Lixia Yao United States 20 189 0.4× 405 0.9× 217 1.1× 68 0.5× 32 0.3× 95 1.2k
Stephen Wu United States 20 781 1.6× 612 1.3× 77 0.4× 153 1.2× 29 0.3× 49 1.3k
Hercules Dalianis Sweden 23 1.3k 2.8× 796 1.7× 133 0.7× 287 2.3× 106 1.1× 124 1.8k
Erik M. van Mulligen Netherlands 29 986 2.0× 1.2k 2.5× 71 0.4× 166 1.3× 109 1.2× 107 1.9k

Countries citing papers authored by Son Doan

Since Specialization
Citations

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

Fields of papers citing papers by Son Doan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Son Doan

This figure shows the co-authorship network connecting the top 25 collaborators of Son Doan. A scholar is included among the top collaborators of Son Doan 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 Son Doan. Son Doan 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.
Doan, Son, Hung Q. Ngo, Ai Kawazoe, & Nigel Collier. (2019). Global Health Monitor: A Web-based System for Detecting and Mapping Infectious Diseases. arXiv (Cornell University). 951–956. 6 indexed citations
2.
Doan, Son, et al.. (2019). Extracting health-related causality from twitter messages using natural language processing. BMC Medical Informatics and Decision Making. 19(S3). 42 indexed citations
3.
Conway, Mike, Danielle L. Mowery, Amy Ising, et al.. (2018). Cross Disciplinary Consultancy to Bridge Public Health Technical Needs and Analytic Developers: Negation Detection Use Case. Online Journal of Public Health Informatics. 10(2). e209–e209. 2 indexed citations
4.
Doan, Son, Cleo K. Maehara, Juan D. Chaparro, et al.. (2016). Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes. Academic Emergency Medicine. 23(5). 628–636. 39 indexed citations
5.
Conway, Mike, et al.. (2015). Crowdsourcing Twitter annotations to identify first-hand experiences of prescription drug use. Journal of Biomedical Informatics. 58. 280–287. 55 indexed citations
6.
Doan, Son, Mike Conway, Lucila Ohno‐Machado, et al.. (2013). PhenDisco: phenotype discovery system for the database of genotypes and phenotypes. Journal of the American Medical Informatics Association. 21(1). 31–36. 6 indexed citations
7.
Jiang, Xiaoqian, et al.. (2013). Recent trends in biomedical informatics: a study based onJAMIAarticles. Journal of the American Medical Informatics Association. 20(e2). e198–e205. 13 indexed citations
8.
Collier, Nigel & Son Doan. (2012). GENI-DB: a database of global events for epidemic intelligence. Bioinformatics. 28(8). 1186–1188. 7 indexed citations
9.
Doan, Son, et al.. (2012). Recognition of medication information from discharge summaries using ensembles of classifiers. BMC Medical Informatics and Decision Making. 12(1). 36–36. 35 indexed citations
10.
Xu, Hua, Samir Abdelrahman, Yanxin Lu, Joshua C. Denny, & Son Doan. (2011). Applying semantic-based probabilistic context-free grammar to medical language processing – A preliminary study on parsing medication sentences. Journal of Biomedical Informatics. 44(6). 1068–1075. 4 indexed citations
11.
Xu, Hanzhang, Shane P. Stenner, Son Doan, et al.. (2010). MedEx: a medication information extraction system for clinical narratives. Journal of the American Medical Informatics Association. 17(1). 19–24. 389 indexed citations
12.
Doan, Son, et al.. (2010). Integrating existing natural language processing tools for medication extraction from discharge summaries. Journal of the American Medical Informatics Association. 17(5). 528–531. 52 indexed citations
13.
Conway, Mike, Son Doan, Ai Kawazoe, & Nigel Collier. (2009). Classifying disease outbreak reports using n-grams and semantic features. International Journal of Medical Informatics. 78(12). e47–e58. 43 indexed citations
14.
Doan, Son, Ai Kawazoe, Mike Conway, & Nigel Collier. (2009). Towards role-based filtering of disease outbreak reports. Journal of Biomedical Informatics. 42(5). 773–780. 12 indexed citations
15.
Conway, Mike, Son Doan, Ai Kawazoe, & Nigel Collier. (2008). Classifying disease outbreak reports using n-grams and semantic features. 5 indexed citations
16.
Collier, Nigel, Son Doan, Ai Kawazoe, et al.. (2008). BioCaster: detecting public health rumors with a Web-based text mining system. Bioinformatics. 24(24). 2940–2941. 170 indexed citations
17.
Doan, Son & Susumu Horiguchi. (2005). An efficient feature selection using multi-criteria in text categorization for naïve Bayes classifier. International Conference on Artificial Intelligence. 34. 5 indexed citations
18.
Doan, Son & Susumu Horiguchi. (2005). Improving Text Categorization by Multicriteria Feature Selection. Journal of Advanced Computational Intelligence and Intelligent Informatics. 9(5). 570–575. 1 indexed citations
19.
Doan, Son, et al.. (2004). An Agent-Based Approach to Feature Selection in Text Categorization. 3 indexed citations
20.
Doan, Son & Susumu Horiguchi. (2002). A new text representation method using fuzzy concepts in text categorization. JAIST Repository. 2002. 1–14.

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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