Jenny Yang

1.6k total citations · 1 hit paper
17 papers, 968 citations indexed

About

Jenny Yang is a scholar working on Artificial Intelligence, Health Informatics and Molecular Biology. According to data from OpenAlex, Jenny Yang has authored 17 papers receiving a total of 968 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Health Informatics and 4 papers in Molecular Biology. Recurrent topics in Jenny Yang's work include Artificial Intelligence in Healthcare and Education (5 papers), COVID-19 diagnosis using AI (4 papers) and Machine Learning in Healthcare (3 papers). Jenny Yang is often cited by papers focused on Artificial Intelligence in Healthcare and Education (5 papers), COVID-19 diagnosis using AI (4 papers) and Machine Learning in Healthcare (3 papers). Jenny Yang collaborates with scholars based in United Kingdom, China and United States. Jenny Yang's co-authors include Xueliang Gao, Xiaowei Liu, Zhi‐Ren Liu, Haizhen Wang, David A. Clifton, Andrew A. S. Soltan, David W. Eyre, Yang Yang, Lei Lü and Nguyễn Thanh Phong and has published in prestigious journals such as Nature Communications, Molecular Cell and Scientific Reports.

In The Last Decade

Jenny Yang

17 papers receiving 954 citations

Hit Papers

align trajectories

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.

Pyruvate Kinase M2 Regulates Gene Transcription by Acting as a Protein Kinase

2012 611 citations Xueliang Gao, Haizhen Wang et al. Molecular Cell profile →

Peers

Jenny Yang

ONCOL

IMMUN

Boris Oskotsky United States

Daniel Ziemek United States

Ryan Goosen Switzerland

Michael P. Menden Germany

Sijia Huang United States

Saumya Shekhar Jamuar Singapore

Ken Asada Japan

Wei‐Yi Cheng United States

Nicholas C. Spies United States

Fiorella Guadagni Italy

Boris Oskotsky United States

Jenny Yang

313 ×0.6

151 ×0.4

120 ×1.0

122 ×1.2

ONCOL

73 ×0.8

IMMUN

Citations per year, relative to Jenny Yang Jenny Yang (= 1×) peers Boris Oskotsky

Countries citing papers authored by Jenny Yang

Since Specialization

Citations

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

Fields of papers citing papers by Jenny Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jenny Yang

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

All Works

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17 of 17 papers shown

Yang, Jenny, et al.. (2024). Addressing label noise for electronic health records: insights from computer vision for tabular data. BMC Medical Informatics and Decision Making. 24(1). 183–183. 4 indexed citations

Yang, Jenny, Nguyen Thanh Dung, Phạm Ngọc Thạch, et al.. (2024). Generalizability assessment of AI models across hospitals in a low-middle and high income country. Nature Communications. 15(1). 8270–8270. 26 indexed citations

Yang, Jenny, Lei Clifton, Nguyen Thanh Dung, et al.. (2024). Mitigating machine learning bias between high income and low–middle income countries for enhanced model fairness and generalizability. Scientific Reports. 14(1). 13318–13318. 11 indexed citations

Soltan, Andrew A. S., Jenny Yang, Anoop Chauhan, et al.. (2024). A scalable federated learning solution for secondary care using low-cost microcomputing: privacy-preserving development and evaluation of a COVID-19 screening test in UK hospitals. The Lancet Digital Health. 6(2). e93–e104. 20 indexed citations

Lü, Lei, Tingting Zhu, Davide Morelli, et al.. (2023). Uncertainties in the Analysis of Heart Rate Variability: A Systematic Review. IEEE Reviews in Biomedical Engineering. 17. 180–196. 9 indexed citations

Yang, Jenny, Alexander S. Lachapelle, Andrew A. S. Soltan, et al.. (2023). Deep reinforcement learning for multi-class imbalanced training: applications in healthcare. Machine Learning. 113(5). 2655–2674. 24 indexed citations

Yang, Jenny, David W. Eyre, Lei Lü, & David A. Clifton. (2023). Interpretable machine learning-based decision support for prediction of antibiotic resistance for complicated urinary tract infections. PubMed. 1(1). 14–14. 9 indexed citations

Yang, Jenny, Andrew A. S. Soltan, David W. Eyre, Yang Yang, & David A. Clifton. (2023). An adversarial training framework for mitigating algorithmic biases in clinical machine learning. npj Digital Medicine. 6(1). 55–55. 58 indexed citations

Lu, Huiqi, Xiaorong Ding, Jane E. Hirst, et al.. (2023). Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes. IEEE Reviews in Biomedical Engineering. 17. 98–117. 19 indexed citations

10.

Yang, Jenny, Andrew A. S. Soltan, David W. Eyre, & David A. Clifton. (2023). Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning. Nature Machine Intelligence. 5(8). 884–894. 56 indexed citations

11.

Yang, Jenny, Andrew A. S. Soltan, & David A. Clifton. (2022). Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening. npj Digital Medicine. 5(1). 69–69. 89 indexed citations

12.

Yang, Jenny, et al.. (2022). Machine Learning-Based Risk Stratification for Gestational Diabetes Management. Sensors. 22(13). 4805–4805. 8 indexed citations

13.

Kouchaki, Samaneh, et al.. (2022). Privacy-Aware Early Detection of COVID-19 Through Adversarial Training. IEEE Journal of Biomedical and Health Informatics. 27(3). 1249–1258. 3 indexed citations

14.

Miller, Cassandra, et al.. (2017). Monitoring ER/SR Calcium Release with the Targeted Ca<sup>2+</sup> Sensor CatchER<sup>+</sup>. Journal of Visualized Experiments. 1 indexed citations

15.

Chen, Yanyi, Shenghui Xue, Juan Zou, et al.. (2014). Myoplasmic resting Ca2+ regulation by ryanodine receptors is under the control of a novel Ca2+-binding region of the receptor. Biochemical Journal. 460(2). 261–271. 11 indexed citations

16.

Gao, Xueliang, Haizhen Wang, Jenny Yang, Xiaowei Liu, & Zhi‐Ren Liu. (2012). Pyruvate Kinase M2 Regulates Gene Transcription by Acting as a Protein Kinase. Molecular Cell. 45(5). 598–609. 611 indexed citations breakdown →

17.

Kirberger, Michael, Xue Wang, Kun Zhao, et al.. (2010). Integration of Diverse Research Methods to Analyze and Engineer Ca2+- Binding Proteins: From Prediction to Production. Current Bioinformatics. 5(1). 68–80. 9 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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