Haijun Zhai

640 total citations
19 papers, 464 citations indexed

About

Haijun Zhai is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology. According to data from OpenAlex, Haijun Zhai has authored 19 papers receiving a total of 464 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 6 papers in Information Systems and 4 papers in Molecular Biology. Recurrent topics in Haijun Zhai's work include Topic Modeling (6 papers), Web Data Mining and Analysis (5 papers) and Biomedical Text Mining and Ontologies (4 papers). Haijun Zhai is often cited by papers focused on Topic Modeling (6 papers), Web Data Mining and Analysis (5 papers) and Biomedical Text Mining and Ontologies (4 papers). Haijun Zhai collaborates with scholars based in United States and China. Haijun Zhai's co-authors include Imre Solti, Todd Lingren, Qi Li, Megan Kaiser, Yizhao Ni, Louise Deléger, Laura Stoutenborough, Eric S. Kirkendall, Patrick W. Brady and Derek S. Wheeler and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Medical Internet Research and Journal of the American Medical Informatics Association.

In The Last Decade

Haijun Zhai

18 papers receiving 448 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Haijun Zhai United States 11 201 120 82 51 48 19 464
Leonard DʼAvolio United States 15 118 0.6× 149 1.2× 90 1.1× 119 2.3× 92 1.9× 32 707
Louise Deléger France 18 521 2.6× 429 3.6× 113 1.4× 28 0.5× 67 1.4× 46 844
Hans Moen Finland 11 464 2.3× 333 2.8× 78 1.0× 32 0.6× 51 1.1× 50 824
Ted Speroff United States 9 80 0.4× 120 1.0× 66 0.8× 30 0.6× 55 1.1× 14 491
Gloria Lipori United States 12 409 2.0× 94 0.8× 131 1.6× 102 2.0× 78 1.6× 26 1.1k
Imre Solti United States 20 734 3.7× 676 5.6× 224 2.7× 88 1.7× 135 2.8× 35 1.4k
Thomas A. Oniki United States 12 131 0.7× 149 1.2× 164 2.0× 67 1.3× 61 1.3× 20 528
Rosy Tsopra France 13 71 0.4× 43 0.4× 92 1.1× 47 0.9× 61 1.3× 42 401
Rimma Perotte United States 11 340 1.7× 211 1.8× 136 1.7× 138 2.7× 31 0.6× 23 714
Kenneth Lai United States 17 161 0.8× 99 0.8× 83 1.0× 27 0.5× 49 1.0× 27 762

Countries citing papers authored by Haijun Zhai

Since Specialization
Citations

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

Fields of papers citing papers by Haijun Zhai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haijun Zhai

This figure shows the co-authorship network connecting the top 25 collaborators of Haijun Zhai. A scholar is included among the top collaborators of Haijun Zhai 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 Haijun Zhai. Haijun Zhai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Solti, Imre, Eric S. Kirkendall, Haijun Zhai, et al.. (2017). Leveraging Food and Drug Administration Adverse Event Reports for the Automated Monitoring of Electronic Health Records in a Pediatric Hospital. SHILAP Revista de lepidopterología. 9. 2718907429–2718907429. 16 indexed citations
2.
Li, Qi, Eric S. Kirkendall, Eric S. Hall, et al.. (2015). Automated detection of medication administration errors in neonatal intensive care. Journal of Biomedical Informatics. 57. 124–133. 27 indexed citations
3.
Zhai, Haijun, Patrick W. Brady, Qi Li, et al.. (2014). Developing and evaluating a machine learning based algorithm to predict the need of pediatric intensive care unit transfer for newly hospitalized children. Resuscitation. 85(8). 1065–1071. 64 indexed citations
4.
Li, Qian, Kristin Melton, Todd Lingren, et al.. (2014). Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care. Journal of the American Medical Informatics Association. 21(5). 776–784. 42 indexed citations
5.
Ni, Yizhao, Stephanie Kennebeck, Judith W. Dexheimer, et al.. (2014). Automated clinical trial eligibility prescreening: increasing the efficiency of patient identification for clinical trials in the emergency department. Journal of the American Medical Informatics Association. 22(1). 166–178. 76 indexed citations
6.
Deléger, Louise, Haijun Zhai, Qi Li, et al.. (2013). Developing and evaluating an automated appendicitis risk stratification algorithm for pediatric patients in the emergency department. Journal of the American Medical Informatics Association. 20(e2). e212–e220. 38 indexed citations
7.
Li, Qi, Louise Deléger, Todd Lingren, et al.. (2013). Mining FDA drug labels for medical conditions. BMC Medical Informatics and Decision Making. 13(1). 53–53. 26 indexed citations
8.
Lingren, Todd, Louise Deléger, Haijun Zhai, et al.. (2013). Evaluating the impact of pre-annotation on annotation speed and potential bias: natural language processing gold standard development for clinical named entity recognition in clinical trial announcements. Journal of the American Medical Informatics Association. 21(3). 406–413. 59 indexed citations
9.
Zhai, Haijun, Todd Lingren, Louise Deléger, et al.. (2013). Web 2.0-Based Crowdsourcing for High-Quality Gold Standard Development in Clinical Natural Language Processing. Journal of Medical Internet Research. 15(4). e73–e73. 52 indexed citations
10.
Zhai, Haijun, et al.. (2013). Predicting Breast Cancer Patient Survival Using Machine Learning. 704–705. 7 indexed citations
11.
Li, Qi, Haijun Zhai, Louise Deléger, et al.. (2012). A sequence labeling approach to link medications and their attributes in clinical notes and clinical trial announcements for information extraction. Journal of the American Medical Informatics Association. 20(5). 915–921. 18 indexed citations
12.
13.
Liu, Jianxun, et al.. (2012). Web Page Recognition Algorithm Based on Link Analysis in Theme Search Engine. 20. 405–409. 4 indexed citations
14.
15.
Liu, Xiangtao, et al.. (2010). Identifying vulgar content in eMule network through text classification. 168–168. 1 indexed citations
16.
Zhai, Haijun, Xueqi Cheng, Jiafeng Guo, Hongbo Xu, & Yue Liu. (2009). A Novel Framework for Related Entities Finding: ICTNET at TREC 2009 Entity Track. Text REtrieval Conference. 11 indexed citations
17.
Zhai, Haijun, et al.. (2009). Query Classification Based on Regularized Correlated Topic Model. 3. 552–555. 8 indexed citations
18.
Wu, Qiong, et al.. (2009). SentiRank: Cross-Domain Graph Ranking for Sentiment Classification. 309–314. 10 indexed citations
19.
Zhai, Haijun, Jin Zhang, Xiaolei Wang, & Gang Zhang. (2008). Mining Related Queries from Query Logs Based on Linear Regression. 665–670. 2 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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