Zhihui Fei

695 total citations
11 papers, 495 citations indexed

About

Zhihui Fei is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Zhihui Fei has authored 11 papers receiving a total of 495 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Artificial Intelligence and 3 papers in Computational Theory and Mathematics. Recurrent topics in Zhihui Fei's work include Machine Learning in Healthcare (3 papers), Biomedical Text Mining and Ontologies (3 papers) and Computational Drug Discovery Methods (3 papers). Zhihui Fei is often cited by papers focused on Machine Learning in Healthcare (3 papers), Biomedical Text Mining and Ontologies (3 papers) and Computational Drug Discovery Methods (3 papers). Zhihui Fei collaborates with scholars based in China, Canada and United States. Zhihui Fei's co-authors include Min Li, Jianxin Wang, Fang‐Xiang Wu, Min Zeng, Yi Pan, Yaohang Li, Ying Yu, Qun Wan, Lie Zhang and Haoying Li and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing and Journal of Rural Studies.

In The Last Decade

Zhihui Fei

11 papers receiving 484 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhihui Fei China	9	269	208	96	57	53	11	495
Zhiheng Li China	11	136 0.5×	170 0.8×	29 0.3×	23 0.4×	30 0.6×	25	478
Po-Yen Wu United States	10	246 0.9×	106 0.5×	96 1.0×	88 1.5×	12 0.2×	23	556
Ester Pantaleo Italy	13	69 0.3×	114 0.5×	18 0.2×	7 0.1×	21 0.4×	36	447
Yanqi Xie China	9	144 0.5×	65 0.3×	6 0.1×	49 0.9×	5 0.1×	26	375
Norberto Corral Spain	17	26 0.1×	219 1.1×	17 0.2×	12 0.2×	12 0.2×	46	658
Hongyan Zhou China	10	242 0.9×	34 0.2×	8 0.1×	15 0.3×	44 0.8×	30	399
Mogana Darshini Ganggayah Malaysia	7	62 0.2×	186 0.9×	69 0.7×	30 0.5×	5 0.1×	14	340
Monica Chiogna Italy	13	199 0.7×	62 0.3×	5 0.1×	44 0.8×	27 0.5×	47	537
Md. Saifur Rahman Bangladesh	8	14 0.1×	140 0.7×	72 0.8×	3 0.1×	6 0.1×	26	434
Weiqi Xia China	7	242 0.9×	22 0.1×	5 0.1×	53 0.9×	64 1.2×	10	385

Countries citing papers authored by Zhihui Fei

Since Specialization

Citations

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

Fields of papers citing papers by Zhihui Fei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhihui Fei

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

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

Lv, Fengmao, Liang Tao, Zhihui Fei, & Wenya Wang. (2022). Progressive Multigranularity Information Propagation for Coupled Aspect-Opinion Extraction. IEEE Transactions on Neural Networks and Learning Systems. 35(6). 7577–7586. 2 indexed citations

Zeng, Min, Chengqian Lu, Zhihui Fei, et al.. (2020). DMFLDA: A Deep Learning Framework for Predicting lncRNA–Disease Associations. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 18(6). 2353–2363. 48 indexed citations

Wu, Yifan, Min Zeng, Zhihui Fei, et al.. (2020). KAICD: A knowledge attention-based deep learning framework for automatic ICD coding. Neurocomputing. 469. 376–383. 21 indexed citations

Yu, Ying, Min Li, Liangliang Liu, et al.. (2019). Automatic ICD code assignment of Chinese clinical notes based on multilayer attention BiRNN. Journal of Biomedical Informatics. 91. 103114–103114. 49 indexed citations

Zeng, Min, Min Li, Zhihui Fei, et al.. (2019). A Deep Learning Framework for Identifying Essential Proteins by Integrating Multiple Types of Biological Information. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 18(1). 296–305. 80 indexed citations

Liu, Liangliang, Ying Yu, Zhihui Fei, et al.. (2018). An interpretable boosting model to predict side effects of analgesics for osteoarthritis. BMC Systems Biology. 12(S6). 105–105. 40 indexed citations

Zeng, Min, Min Li, Zhihui Fei, et al.. (2018). Automatic ICD-9 coding via deep transfer learning. Neurocomputing. 324. 43–50. 79 indexed citations

Zeng, Min, Min Li, Zhihui Fei, et al.. (2018). A Deep Learning Framework for Identifying Essential Proteins Based on Protein-Protein Interaction Network and Gene Expression Data. 2005. 583–588. 12 indexed citations

Li, Min, Zhihui Fei, Min Zeng, et al.. (2018). Automated ICD-9 Coding via A Deep Learning Approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 16(4). 1193–1202. 97 indexed citations

10.

Liu, Liangliang, Jianxin Wang, Min Li, et al.. (2017). An interpretable model for predicting side effects of analgesics for osteoarthritis. 15. 861–864. 1 indexed citations

11.

Wang, Cheng, Bo Huang, Chun Deng, et al.. (2016). Rural settlement restructuring based on analysis of the peasant household symbiotic system at village level: A Case Study of Fengsi Village in Chongqing, China. Journal of Rural Studies. 47. 485–495. 66 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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