Qiubin Yu

401 total citations
10 papers, 251 citations indexed

About

Qiubin Yu is a scholar working on Artificial Intelligence, Molecular Biology and Surgery. According to data from OpenAlex, Qiubin Yu has authored 10 papers receiving a total of 251 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 8 papers in Molecular Biology and 1 paper in Surgery. Recurrent topics in Qiubin Yu's work include Biomedical Text Mining and Ontologies (8 papers), Topic Modeling (8 papers) and Machine Learning in Healthcare (5 papers). Qiubin Yu is often cited by papers focused on Biomedical Text Mining and Ontologies (8 papers), Topic Modeling (8 papers) and Machine Learning in Healthcare (5 papers). Qiubin Yu collaborates with scholars based in China, United States and Australia. Qiubin Yu's co-authors include Yi Guan, Jinfeng Yang, Xishuang Dong, Lijun Qian, Xiangfang Li, Jingchi Jiang, Lei Huang, Xueli Li, Jing Xie and Xitong Guo and has published in prestigious journals such as PLoS ONE, BMC Bioinformatics and Physica A Statistical Mechanics and its Applications.

In The Last Decade

Qiubin Yu

10 papers receiving 247 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Qiubin Yu China	8	184	99	29	26	19	10	251
Cho-Tsan Bau Taiwan	6	108 0.6×	54 0.5×	51 1.8×	10 0.4×	13 0.7×	9	197
Mani Abedini Australia	8	125 0.7×	31 0.3×	20 0.7×	2 0.1×	4 0.2×	18	213
Bin Ji China	10	167 0.9×	67 0.7×	7 0.2×	14 0.5×	1 0.1×	37	240
Hunter Lang United States	3	113 0.6×	16 0.2×	14 0.5×	7 0.3×		6	150
Sunil Mohan United States	7	120 0.7×	73 0.7×	4 0.1×	11 0.4×		9	183
Muchao Ye United States	8	249 1.4×	43 0.4×	118 4.1×	6 0.2×		13	283
Martina Iammarino Italy	9	54 0.3×	13 0.1×	39 1.3×	7 0.3×	5 0.3×	31	243
Jordi Armengol-Estapé Spain	8	111 0.6×	53 0.5×	8 0.3×	11 0.4×		16	139
Hidetaka Nambo Japan	8	39 0.2×	29 0.3×	5 0.2×	2 0.1×	19 1.0×	68	184
Shan Zhao China	7	180 1.0×	36 0.4×	8 0.3×	28 1.1×		16	238

Countries citing papers authored by Qiubin Yu

Since Specialization

Citations

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

Fields of papers citing papers by Qiubin Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qiubin Yu

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

All Works

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10 of 10 papers shown

1.

Jiang, Jingchi, et al.. (2019). Medical knowledge embedding based on recursive neural network for multi-disease diagnosis. Artificial Intelligence in Medicine. 103. 101772–101772. 21 indexed citations

2.

Dong, Xishuang, Lijun Qian, Xiangfang Li, et al.. (2019). Deep learning for named entity recognition on Chinese electronic medical records: Combining deep transfer learning with multitask bi-directional LSTM RNN. PLoS ONE. 14(5). e0216046–e0216046. 36 indexed citations

3.

Dong, Xishuang, Lijun Qian, Xiangfang Li, et al.. (2018). A multitask bi-directional RNN model for named entity recognition on Chinese electronic medical records. BMC Bioinformatics. 19(S17). 499–499. 48 indexed citations

4.

Jiang, Jingchi, et al.. (2018). Max-margin weight learning for medical knowledge network. Computer Methods and Programs in Biomedicine. 156. 179–190. 3 indexed citations

5.

He, Bin, et al.. (2017). Building a comprehensive syntactic and semantic corpus of Chinese clinical texts. Journal of Biomedical Informatics. 69. 203–217. 35 indexed citations

6.

Dong, Xishuang, et al.. (2017). Transfer bi-directional LSTM RNN for named entity recognition in Chinese electronic medical records. 1–4. 20 indexed citations

7.

Jiang, Jingchi, et al.. (2017). Learning and inference in knowledge-based probabilistic model for medical diagnosis. Knowledge-Based Systems. 138. 58–68. 20 indexed citations

8.

Dong, Xishuang, Lijun Qian, Yi Guan, et al.. (2016). A multiclass classification method based on deep learning for named entity recognition in electronic medical records. 1–10. 44 indexed citations

9.

Jiang, Jingchi, et al.. (2016). Clinical-decision support based on medical literature: A complex network approach. Physica A Statistical Mechanics and its Applications. 459. 42–54. 5 indexed citations

10.

Zhang, Huiying, Wei Xia, Qiubin Yu, et al.. (2008). Increasing incidence of type 1 diabetes in children aged 0–14 years in Harbin, China (1990–2000). Primary care diabetes. 2(3). 121–126. 19 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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