Shuntaro Yada

485 total citations
47 papers, 242 citations indexed

About

Shuntaro Yada is a scholar working on Artificial Intelligence, Molecular Biology and Toxicology. According to data from OpenAlex, Shuntaro Yada has authored 47 papers receiving a total of 242 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 15 papers in Molecular Biology and 8 papers in Toxicology. Recurrent topics in Shuntaro Yada's work include Topic Modeling (17 papers), Biomedical Text Mining and Ontologies (15 papers) and Natural Language Processing Techniques (9 papers). Shuntaro Yada is often cited by papers focused on Topic Modeling (17 papers), Biomedical Text Mining and Ontologies (15 papers) and Natural Language Processing Techniques (9 papers). Shuntaro Yada collaborates with scholars based in Japan, Australia and Canada. Shuntaro Yada's co-authors include Eiji Aramaki, Shoko Wakamiya, Yuta Nakamura, Kyo Kageura, Keiichiro Hoashi, Kazushi Ikeda, Satoko Hori, Kota Tsubouchi, Sumio Fujita and Satoshi Nishioka and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Medical Internet Research.

In The Last Decade

Shuntaro Yada

39 papers receiving 239 citations

Peers

Shuntaro Yada
Sicheng Zhou United States
Serena Jeblee Canada
Megan Kaiser United States
Jennifer J. Liang United States
Yassine Mrabet United States
Yasuhide Miura Japan
Anthony Rios United States
Ergin Soysal United States
Jungwei Fan United States
Lewis J. Frey United States
Sicheng Zhou United States
Shuntaro Yada
Citations per year, relative to Shuntaro Yada Shuntaro Yada (= 1×) peers Sicheng Zhou

Countries citing papers authored by Shuntaro Yada

Since Specialization
Citations

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

Fields of papers citing papers by Shuntaro Yada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuntaro Yada

This figure shows the co-authorship network connecting the top 25 collaborators of Shuntaro Yada. A scholar is included among the top collaborators of Shuntaro Yada 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 Shuntaro Yada. Shuntaro Yada 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.
Shimizu, Seiji, et al.. (2025). RecordTwin: Towards Creating Safe Synthetic Clinical Corpora. 14714–14726.
2.
Yada, Shuntaro, et al.. (2025). GenKP: generative knowledge prompts for enhancing large language models. Applied Intelligence. 55(7). 1 indexed citations
3.
Tsuchiya, Masami, Yoshimasa Kawazoe, Tomohisa Seki, et al.. (2025). Elucidating Celecoxib's Preventive Effect in Capecitabine-Induced Hand-Foot Syndrome Using Medical Natural Language Processing. JCO Clinical Cancer Informatics. 9(9). e2500096–e2500096.
4.
Yada, Shuntaro, Shoko Wakamiya, Yoshimasa Kawazoe, et al.. (2024). Utility analysis and demonstration of real-world clinical texts: A case study on Japanese cancer-related EHRs. PLoS ONE. 19(9). e0310432–e0310432. 3 indexed citations
5.
Nishioka, Satoshi, Satoshi Watabe, K Sayama, et al.. (2024). Adverse Event Signal Detection Using Patients’ Concerns in Pharmaceutical Care Records: Evaluation of Deep Learning Models. Journal of Medical Internet Research. 26. e55794–e55794. 3 indexed citations
6.
Sato, Rie, Masami Tsuchiya, Satoshi Watabe, et al.. (2024). Analysis of Overdose-related Posts on Social Media. YAKUGAKU ZASSHI. 144(12). 1125–1135. 1 indexed citations
7.
Kawazoe, Yoshimasa, Tomohisa Seki, Masami Tsuchiya, et al.. (2024). Post-marketing surveillance of anticancer drugs using natural language processing of electronic medical records. npj Digital Medicine. 7(1). 315–315. 3 indexed citations
8.
Yada, Shuntaro, et al.. (2024). Assessing domain adaptation in adverse drug event extraction on real-world breast cancer records. International Journal of Medical Informatics. 191. 105539–105539. 3 indexed citations
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Yamauchi, Takahira, et al.. (2023). Diagnosing psychiatric disorders from history of present illness using a large‐scale linguistic model. Psychiatry and Clinical Neurosciences. 77(11). 597–604. 6 indexed citations
12.
Yada, Shuntaro, et al.. (2023). Transferability Based on Drug Structure Similarity in the Automatic Classification of Noncompliant Drug Use on Social Media: Natural Language Processing Approach. Journal of Medical Internet Research. 25. e44870–e44870. 3 indexed citations
13.
Nishioka, Satoshi, Masaki Asano, Shuntaro Yada, et al.. (2023). Adverse event signal extraction from cancer patients’ narratives focusing on impact on their daily-life activities. Scientific Reports. 13(1). 15516–15516. 2 indexed citations
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Yada, Shuntaro, et al.. (2022). Identifying A Target Scope of Complaints on Social Media. 111–118.
16.
Fujita, Sumio, et al.. (2021). Measuring Public Concern About COVID-19 in Japanese Internet Users Through Search Queries: Infodemiological Study. JMIR Public Health and Surveillance. 7(7). e29865–e29865. 3 indexed citations
17.
Wakamiya, Shoko, et al.. (2021). Medical Needs Extraction for Breast Cancer Patients from Question and Answer Services: Natural Language Processing-Based Approach. JMIR Cancer. 7(4). e32005–e32005. 5 indexed citations
18.
Yada, Shuntaro, et al.. (2020). A Preliminary Analysis of Offensive Language Transferability from Social Media to Video Live Streaming. 2020. 1 indexed citations
19.
Yada, Shuntaro, et al.. (2020). Towards a Versatile Medical-Annotation Guideline Feasible Without Heavy Medical Knowledge: Starting From Critical Lung Diseases. Language Resources and Evaluation. 4565–4572. 4 indexed citations
20.
Yada, Shuntaro, et al.. (2020). Identification of Adverse Drug Event–Related Japanese Articles: Natural Language Processing Analysis. JMIR Medical Informatics. 8(11). e22661–e22661. 13 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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