Son Doan

1.8k citations
43 papers · 1.4k · h-index 16

Impact in

Papers in

    • Text and Document Classification Technologies 13
    • Sentiment Analysis and Opinion Mining 4
    • Semantic Web and Ontologies 2
    • Privacy-Preserving Technologies in Data 1
    • Biomedical Text Mining and Ontologies 20

Son Doan

41 papers receiving 1.3k citations

Peers

Son Doan
Comparison fields: 5 of 110
  • Health Information Management 192
  • Toxicology 103
  • Artificial Intelligence 500
  • Health Informatics 30
  • Molecular Biology 452
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Citations per field
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Citations per year

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-authors

The 25 scholars most cited alongside Son Doan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Son Doan Line = papers co-authored together Son Doan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010432
2 2008199
3 201479
4 201568
5 201066
6 201257
7 201956
8 201454
9 200948
10 201640
11 201237
12
Recognizing Medication related Entities in Hospital Discharge Summaries using Support Vector Machine.
201031
13 201230
14
Ensembles of NLP Tools for Data Element Extraction from Clinical Notes.
201622
15
An ontology-driven system for detecting global health events
201016
16 201616
17 201315
18 200914
19
An automated approach to calculating the daily dose of tacrolimus in electronic health records.
201011
20 200510

About Son Doan

Son Doan is a scholar working on Artificial Intelligence, Molecular Biology, Epidemiology, Health Informatics and Toxicology, having authored 43 papers that have together received 1.4k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (20 papers), Text and Document Classification Technologies (13 papers), Data-Driven Disease Surveillance (7 papers), Sentiment Analysis and Opinion Mining (4 papers), Semantic Web and Ontologies (2 papers), Electronic Health Records Systems (1 paper), Privacy-Preserving Technologies in Data (1 paper) and Artificial Intelligence in Healthcare and Education (1 paper). The work is most often cited by research in Health Information Management (192 citations), Toxicology (103 citations), Artificial Intelligence (500 citations), Health Informatics (30 citations) and Molecular Biology (452 citations). Son Doan has collaborated with scholars based in United States, Japan and Vietnam. Frequent co-authors include Nigel Collier, Joshua C. Denny, Shane P. Stenner, Lemuel Russell Waitman, Hanzhang Xu, Mike Conway, Hua Xu, Ai Kawazoe, Lucila Ohno‐Machado and Hung Q. Ngo. Their work appears in journals such as Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, Bioinformatics, BMC Medical Informatics and Decision Making and Academic Emergency Medicine.

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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