Ke Yu

1.2k total citations · 1 hit paper
39 papers, 830 citations indexed

About

Ke Yu is a scholar working on Artificial Intelligence, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ke Yu has authored 39 papers receiving a total of 830 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 7 papers in Molecular Biology and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ke Yu's work include Advanced Memory and Neural Computing (5 papers), COVID-19 diagnosis using AI (5 papers) and Neural Networks and Applications (5 papers). Ke Yu is often cited by papers focused on Advanced Memory and Neural Computing (5 papers), COVID-19 diagnosis using AI (5 papers) and Neural Networks and Applications (5 papers). Ke Yu collaborates with scholars based in United States, China and Hong Kong. Ke Yu's co-authors include Weida Tong, Minjun Chen, Tong Zhang, Ayako Suzuki, Shraddha Thakkar, Kayhan Batmanghelich, Yu Xia, Daniel T. W. Tang, Herbert H. P. Fang and Frankie Tat Kwong Lau and has published in prestigious journals such as PLoS ONE, Journal of Cleaner Production and The American Journal of Human Genetics.

In The Last Decade

Ke Yu

31 papers receiving 812 citations

Hit Papers

DILIrank: the largest reference drug list ranked by the r... 2016 2026 2019 2022 2016 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. DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans
    2016 267 citations Minjun Chen, Ayako Suzuki et al. Drug Discovery Today profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ke Yu United States 11 226 205 167 107 104 39 830
Weiwei Cao China 19 59 0.3× 293 1.4× 31 0.2× 61 0.6× 100 1.0× 63 1.1k
Qiao Xue China 21 65 0.3× 418 2.0× 106 0.6× 90 0.8× 97 0.9× 96 1.4k
Peng Yin China 15 39 0.2× 181 0.9× 117 0.7× 28 0.3× 51 0.5× 58 624
Xiaohu Ren China 16 27 0.1× 322 1.6× 100 0.6× 59 0.6× 33 0.3× 74 860
Yuxin Wang China 24 93 0.4× 545 2.7× 34 0.2× 33 0.3× 68 0.7× 72 1.6k
Devvret Verma India 15 27 0.1× 175 0.9× 68 0.4× 31 0.3× 102 1.0× 74 904
Jinglin Yang China 12 62 0.3× 695 3.4× 526 3.1× 51 0.5× 55 0.5× 29 1.1k

Countries citing papers authored by Ke Yu

Since Specialization
Citations

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

Fields of papers citing papers by Ke Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ke Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Ke Yu. A scholar is included among the top collaborators of Ke 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 Ke Yu. Ke Yu 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
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Duan, Yuanyuan, Jiaxin Chen, Xiaoting Huang, et al.. (2025). Systematic functional characterization of non-coding regulatory SNPs associated with central obesity. The American Journal of Human Genetics. 112(1). 116–134.
3.
Yu, Ke, et al.. (2025). STAA-SNN: Spatial-Temporal Attention Aggregator for Spiking Neural Networks. 13959–13969. 1 indexed citations
4.
Zhang, Tianqing, Ke Yu, Jian Zhang, & Hongwei Wang. (2025). DA-LIF: Dual Adaptive Leaky Integrate-and-Fire Model for Deep Spiking Neural Networks. 1–5.
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Dong, Shan‐Shan, Wei Huang, Hairong Wang, et al.. (2025). Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases. Cardiovascular Diabetology. 24(1). 312–312. 1 indexed citations
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Zhou, Yuhao, et al.. (2024). PSC-BERT: A spam identification and classification algorithm via prompt learning and spell check. Knowledge-Based Systems. 301. 112266–112266. 4 indexed citations
8.
Yu, Ke, et al.. (2024). Anatomy-specific Progression Classification in Chest Radiographs via Weakly Supervised Learning. Radiology Artificial Intelligence. 6(5). e230277–e230277.
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Yu, Ke, et al.. (2023). DrasCLR: A self-supervised framework of learning disease-related and anatomy-specific representation for 3D lung CT images. Medical Image Analysis. 92. 103062–103062. 14 indexed citations
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Yu, Ke, et al.. (2023). Distilling BlackBox to Interpretable Models for Efficient Transfer Learning. Lecture notes in computer science. 14221. 628–638.
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Chen, Junxiang, Zhonghui Xu, Li Sun, et al.. (2023). Deep Learning Integration of Chest Computed Tomography Imaging and Gene Expression Identifies Novel Aspects of COPD. Chronic Obstructive Pulmonary Diseases Journal of the COPD Foundation. 10(4). 355–368. 5 indexed citations
15.
Yu, Ke, et al.. (2019). Monitoring ICU Mortality Risk with A Long Short-Term Memory Recurrent Neural Network. PubMed. 25. 103–114. 26 indexed citations
16.
Chen, Minjun, et al.. (2016). DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans. Drug Discovery Today. 21(4). 648–653. 267 indexed citations breakdown →
17.
Yang, Ying, Ke Yu, Yu Xia, et al.. (2014). Metagenomic analysis of sludge from full-scale anaerobic digesters operated in municipal wastewater treatment plants. Applied Microbiology and Biotechnology. 98(12). 5709–5718. 173 indexed citations
18.
Yu, Ke, Xingchao Geng, Minjun Chen, et al.. (2014). High Daily Dose and Being a Substrate of Cytochrome P450 Enzymes Are Two Important Predictors of Drug-Induced Liver Injury. Drug Metabolism and Disposition. 42(4). 744–750. 107 indexed citations
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Li, Xue, et al.. (2003). Real time web vehicle classifier. Acquire (CQUniversity). 1. 428–434. 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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