Bei Yang

729 total citations
35 papers, 494 citations indexed

About

Bei Yang is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Bei Yang has authored 35 papers receiving a total of 494 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 6 papers in Molecular Biology and 6 papers in Information Systems. Recurrent topics in Bei Yang's work include AI in cancer detection (4 papers), Sentiment Analysis and Opinion Mining (3 papers) and Data Mining Algorithms and Applications (3 papers). Bei Yang is often cited by papers focused on AI in cancer detection (4 papers), Sentiment Analysis and Opinion Mining (3 papers) and Data Mining Algorithms and Applications (3 papers). Bei Yang collaborates with scholars based in China, United States and Japan. Bei Yang's co-authors include Ping Gong, Chaoyang Zhang, Zhaoxian Zhou, Huixiao Hong, Andrew Maxwell, Runzhi Li, Aihua Ou, Heng Weng, Bingyi Wang and Yanbu Guo and has published in prestigious journals such as Expert Systems with Applications, BMC Bioinformatics and Medical Physics.

In The Last Decade

Bei Yang

34 papers receiving 475 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bei Yang China	13	155	136	89	62	48	35	494
Gamage Upeksha Ganegoda Sri Lanka	10	104 0.7×	161 1.2×	30 0.3×	35 0.6×	18 0.4×	43	493
David B. Blumenthal Germany	13	169 1.1×	218 1.6×	112 1.3×	17 0.3×	105 2.2×	48	544
Renqian Luo China	7	408 2.6×	157 1.2×	45 0.5×	72 1.2×	58 1.2×	10	799
Sayash Kapoor United States	9	153 1.0×	39 0.3×	27 0.3×	29 0.5×	16 0.3×	15	435
Bob J.A. Schijvenaars Netherlands	13	309 2.0×	333 2.4×	48 0.5×	27 0.4×	20 0.4×	25	684
Giovanna Maria Dimitri Italy	12	94 0.6×	81 0.6×	51 0.6×	34 0.5×	55 1.1×	42	374
Michele Filannino United States	11	459 3.0×	290 2.1×	24 0.3×	21 0.3×	42 0.9×	20	722
裕二池谷 United States	10	948 6.1×	534 3.9×	71 0.8×	122 2.0×	90 1.9×	19	1.3k
Naoto Usuyama United States	7	867 5.6×	500 3.7×	63 0.7×	124 2.0×	88 1.8×	14	1.2k

Countries citing papers authored by Bei Yang

Since Specialization

Citations

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

Fields of papers citing papers by Bei Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bei Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Bei Yang. A scholar is included among the top collaborators of Bei Yang 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 Bei Yang. Bei Yang 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:

20 of 20 papers shown

He, Dazhi, et al.. (2024). 6G-Oriented CSI-Based Multi-Modal Pre-Training and Downstream Task Adaptation Paradigm. 1389–1394. 3 indexed citations

Yang, Bei, et al.. (2023). ProMIL: A weakly supervised multiple instance learning for whole slide image classification based on class proxy. Expert Systems with Applications. 238. 121800–121800. 4 indexed citations

Yang, Bei, et al.. (2023). A weakly supervised multi-instance learning based on graph neural network for breast cancer pathology image classification. 47–51. 1 indexed citations

Yang, Bei, et al.. (2023). Multiple instance learning-based two-stage metric learning network for whole slide image classification. The Visual Computer. 40(8). 5717–5732. 5 indexed citations

Li, Shujuan, Jianxiang Shi, Xia Xue, et al.. (2022). Genetic Epidemiology of Medication Safety and Efficacy Related Variants in the Central Han Chinese Population With Whole Genome Sequencing. Frontiers in Pharmacology. 12. 790832–790832. 7 indexed citations

Shi, Lei, et al.. (2022). Topic2Labels: A framework to annotate and classify the social media data through LDA topics and deep learning models for crisis response. Expert Systems with Applications. 195. 116562–116562. 47 indexed citations

Yang, Bei, et al.. (2021). Research on Higher English Internationalization Education Model and Evaluation Index System Based on Multi‐Source Information Fusion. Computational Intelligence and Neuroscience. 2021(1). 1599007–1599007. 5 indexed citations

Shi, Lei, et al.. (2021). Topic2features: a novel framework to classify noisy and sparse textual data using LDA topic distributions. PeerJ Computer Science. 7. e677–e677. 18 indexed citations

Shi, Lei, et al.. (2021). Identifying and Characterizing the Propagation Scale of COVID-19 Situational Information on Twitter: A Hybrid Text Analytic Approach. Applied Sciences. 11(14). 6526–6526. 12 indexed citations

10.

Idakwo, Gabriel, Joseph Luttrell, Yan Li, et al.. (2020). Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets. Journal of Cheminformatics. 12(1). 66–66. 55 indexed citations

11.

Wu, Fa, et al.. (2020). Pulmonary nodule detection using hybrid two‐stage 3D CNNs. Medical Physics. 47(8). 3376–3388. 15 indexed citations

12.

Guo, Yanbu, Bingyi Wang, Weihua Li, & Bei Yang. (2018). Protein secondary structure prediction improved by recurrent neural networks integrated with two-dimensional convolutional neural networks. Journal of Bioinformatics and Computational Biology. 16(5). 1850021–1850021. 49 indexed citations

13.

Maxwell, Andrew, Runzhi Li, Bei Yang, et al.. (2017). Deep learning architectures for multi-label classification of intelligent health risk prediction. BMC Bioinformatics. 18(S14). 523–523. 109 indexed citations

14.

Daimon, Masao, Katsuhisa Ishii, Sakiko Miyazaki, et al.. (2012). A novel global strain diastolic index correlates with plasma NT-proBNP levels in asymptomatic hypertensive patients with preserved left ventricular ejection fraction. Journal of Echocardiography. 10(2). 56–64. 1 indexed citations

15.

Yang, Chunyan, et al.. (2012). Optimization of cryopreservation of buffalo (Bubalus bubalis) blastocysts produced by in vitro fertilization and somatic cell nuclear transfer. Theriogenology. 78(7). 1437–1445. 10 indexed citations

16.

Yang, Chunyan, et al.. (2010). Study on the inter-subspecies nuclear transfer of river buffalo somatic cell nuclei into swamp buffalo oocyte cytoplasm. Animal Reproduction Science. 121(1-2). 78–83. 15 indexed citations

17.

Yang, Bei, et al.. (2010). Mining Top-K Significant Itemsets in Landmark Windows over Data Streams. 47(3). 463. 2 indexed citations

18.

Yang, Bei, et al.. (2008). A modified differential evolution algorithm with self-adaptive control parameters. 22. 524–527. 11 indexed citations

19.

Wu, Zhifeng, et al.. (2008). Adaptive equalization using differential evolution. 11. 1962–1967. 1 indexed citations

20.

Yang, Bei. (2007). An Improved Particle Swarm Optimization Algorithm. Journal of Zhengzhou University. 14 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.

Explore authors with similar magnitude of impact