Yuqi Si

1.6k total citations · 1 hit paper
20 papers, 972 citations indexed

About

Yuqi Si is a scholar working on Artificial Intelligence, Molecular Biology and Sociology and Political Science. According to data from OpenAlex, Yuqi Si has authored 20 papers receiving a total of 972 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 9 papers in Molecular Biology and 2 papers in Sociology and Political Science. Recurrent topics in Yuqi Si's work include Machine Learning in Healthcare (9 papers), Biomedical Text Mining and Ontologies (9 papers) and Topic Modeling (9 papers). Yuqi Si is often cited by papers focused on Machine Learning in Healthcare (9 papers), Biomedical Text Mining and Ontologies (9 papers) and Topic Modeling (9 papers). Yuqi Si collaborates with scholars based in United States, China and Belgium. Yuqi Si's co-authors include Kirk Roberts, Hua Xu, Jingqi Wang, Jingcheng Du, Zongcheng Ji, Stephen Wu, Qiang Wei, Yang Xiang, Bo Zhao and Sarvesh Soni and has published in prestigious journals such as Journal of the American Medical Informatics Association, Fish & Shellfish Immunology and Frontiers in Endocrinology.

In The Last Decade

Yuqi Si

18 papers receiving 950 citations

Hit Papers

Deep learning in clinical natural language processing: a ... 2019 2026 2021 2023 2019 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Deep learning in clinical natural language processing: a methodical review
    2019 291 citations Stephen Wu, Kirk Roberts et al. Journal of the American Medical Informatics Association profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yuqi Si United States 12 556 298 156 128 109 20 972
Dianbo Liu United States 14 507 0.9× 119 0.4× 57 0.4× 20 0.2× 33 1.1k
Hanyin Wang United States 11 272 0.5× 88 0.3× 72 0.5× 11 0.1× 23 602
Stephen Wu United States 20 781 1.4× 612 2.1× 153 1.0× 7 0.1× 49 1.3k
Qiao Jin United States 16 647 1.2× 273 0.9× 63 0.4× 10 0.1× 51 1.2k
Andreas Seyfang United States 23 265 0.5× 753 2.5× 253 1.6× 77 0.6× 2 0.0× 59 2.0k
Dimiter Dimitrov Bulgaria 8 134 0.2× 62 0.2× 88 0.6× 18 0.1× 17 907
Asma Ben Abacha United States 20 1.0k 1.9× 418 1.4× 55 0.4× 9 0.1× 51 1.3k
Il Kon Kim South Korea 11 75 0.1× 33 0.1× 46 0.3× 7 0.1× 26 0.2× 50 425
Fabio Rinaldi Switzerland 20 1.1k 2.0× 869 2.9× 94 0.6× 4 0.0× 141 1.7k

Countries citing papers authored by Yuqi Si

Since Specialization
Citations

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

Fields of papers citing papers by Yuqi Si

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuqi Si

This figure shows the co-authorship network connecting the top 25 collaborators of Yuqi Si. A scholar is included among the top collaborators of Yuqi Si 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 Yuqi Si. Yuqi Si 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.
Si, Yuqi, Lizhu Chen, Yan Zheng, et al.. (2025). The effect of acupuncture on blood glucose control in patients with type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials. Frontiers in Endocrinology. 16. 1596062–1596062. 1 indexed citations
2.
Si, Yuqi, Lihui Wang, & Min Zhao. (2022). Anti-saccade as a Tool to Evaluate Neurocognitive Impairment in Alcohol Use Disorder. Frontiers in Psychiatry. 13. 823848–823848. 7 indexed citations
3.
Si, Yuqi, et al.. (2022). Elevation of serum creatine kinase induced by anti-thyroid drugs: Two case reports and a literature review. International Journal of Clinical Pharmacology and Therapeutics. 60(11). 492–498.
4.
5.
Si, Yuqi, Elmer V. Bernstam, & Kirk Roberts. (2021). Generalized and transferable patient language representation for phenotyping with limited data. Journal of Biomedical Informatics. 116. 103726–103726. 4 indexed citations
6.
Du, Jingcheng, Yang Xiang, Meng Zhang, et al.. (2021). Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning. Journal of the American Medical Informatics Association. 28(7). 1393–1400. 23 indexed citations
7.
Zuo, Yifan, Huan Chen, Jincheng Pan, et al.. (2021). Spatial Distribution Pattern and Influencing Factors of Sports Tourism Resources in China. ISPRS International Journal of Geo-Information. 10(7). 428–428. 48 indexed citations
8.
Champagne‐Langabeer, Tiffany, et al.. (2021). Dramatic Increases in Telehealth-Related Tweets during the Early COVID-19 Pandemic: A Sentiment Analysis. Healthcare. 9(6). 634–634. 5 indexed citations
9.
Si, Yuqi, Jingcheng Du, Li Zhao, et al.. (2020). Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review. Journal of Biomedical Informatics. 115. 103671–103671. 123 indexed citations
10.
Si, Yuqi & Kirk Roberts. (2020). Patient Representation Transfer Learning from Clinical Notes based on Hierarchical Attention Network.. PubMed. 2020. 597–606. 14 indexed citations
11.
Xiang, Yang, Jun Xu, Yuqi Si, et al.. (2019). Time-sensitive clinical concept embeddings learned from large electronic health records. BMC Medical Informatics and Decision Making. 19(S2). 58–58. 24 indexed citations
12.
Wu, Stephen, Kirk Roberts, Surabhi Datta, et al.. (2019). Deep learning in clinical natural language processing: a methodical review. Journal of the American Medical Informatics Association. 27(3). 457–470. 291 indexed citations breakdown →
13.
Si, Yuqi & Kirk Roberts. (2019). Deep Patient Representation of Clinical Notes via Multi-Task Learning for Mortality Prediction.. PubMed. 2019. 779–788. 25 indexed citations
14.
Wei, Qiang, Zongcheng Ji, Yuqi Si, et al.. (2019). Relation Extraction from Clinical Narratives Using Pre-trained Language Models.. PubMed. 2019. 1236–1245. 29 indexed citations
15.
Si, Yuqi, Jingqi Wang, Hua Xu, & Kirk Roberts. (2019). Enhancing clinical concept extraction with contextual embeddings. Journal of the American Medical Informatics Association. 26(11). 1297–1304. 188 indexed citations
16.
Roberts, Kirk, Yuqi Si, Anshul Gandhi, & Elmer V. Bernstam. (2018). A framenet for cancer information in clinical narratives: Schema and annotation. Language Resources and Evaluation. 272–279. 3 indexed citations
17.
Wei, Wei, et al.. (2018). The Data Gap in the EHR for Clinical Research Eligibility Screening.. PubMed. 2017. 320–329. 13 indexed citations
18.
Si, Yuqi & Kirk Roberts. (2018). A Frame-Based NLP System for Cancer-Related Information Extraction.. PubMed. 2018. 1524–1533. 28 indexed citations
19.
Si, Yuqi & Chunhua Weng. (2017). An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria. Studies in health technology and informatics. 245. 950–954. 11 indexed citations
20.

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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