Yu Guan

2.9k total citations · 1 hit paper
81 papers, 1.8k citations indexed

About

Yu Guan is a scholar working on Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Yu Guan has authored 81 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Pulmonary and Respiratory Medicine, 15 papers in Computer Vision and Pattern Recognition and 12 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Yu Guan's work include Chronic Obstructive Pulmonary Disease (COPD) Research (11 papers), Lung Cancer Diagnosis and Treatment (10 papers) and Human Pose and Action Recognition (8 papers). Yu Guan is often cited by papers focused on Chronic Obstructive Pulmonary Disease (COPD) Research (11 papers), Lung Cancer Diagnosis and Treatment (10 papers) and Human Pose and Action Recognition (8 papers). Yu Guan collaborates with scholars based in China, United Kingdom and United States. Yu Guan's co-authors include Thomas Plötz, Shiyuan Liu, Bing Zhai, Jian Qing Shi, Yi Xia, João Palotti, Chang‐Tsun Li, Ignacio Perez-Pozuelo, Rana Zia Ur Rehman and Silvia Del Din and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Yu Guan

74 papers receiving 1.8k citations

Hit Papers

Ensembles of Deep LSTM Learners for Activity Recognition ... 2017 2026 2020 2023 2017 100 200 300
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. Ensembles of Deep LSTM Learners for Activity Recognition using Wearables
    2017 370 citations Yu Guan et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yu Guan China 20 620 370 368 271 250 81 1.8k
Thomas M. Deserno Germany 23 715 1.2× 502 1.4× 408 1.1× 335 1.2× 121 0.5× 187 2.1k
Radim Bürget Czechia 22 554 0.9× 443 1.2× 224 0.6× 557 2.1× 171 0.7× 139 1.8k
Shaikh Anowarul Fattah Bangladesh 25 656 1.1× 635 1.7× 530 1.4× 696 2.6× 217 0.9× 252 2.8k
Giovanna Sannino Italy 19 319 0.5× 573 1.5× 332 0.9× 128 0.5× 159 0.6× 77 1.7k
Charence Wong United Kingdom 10 597 1.0× 679 1.8× 511 1.4× 341 1.3× 90 0.4× 20 2.1k
Dewar Finlay United Kingdom 22 359 0.6× 165 0.4× 486 1.3× 189 0.7× 125 0.5× 217 2.2k
Daniele Ravì Italy 14 764 1.2× 714 1.9× 430 1.2× 407 1.5× 83 0.3× 38 2.2k
Zulfiqar Ali Saudi Arabia 28 427 0.7× 865 2.3× 133 0.4× 142 0.5× 133 0.5× 78 2.1k
Fani Deligianni United Kingdom 18 533 0.9× 565 1.5× 474 1.3× 529 2.0× 98 0.4× 57 2.4k
Sun Kook Yoo South Korea 24 212 0.3× 122 0.3× 694 1.9× 210 0.8× 200 0.8× 141 1.9k

Countries citing papers authored by Yu Guan

Since Specialization
Citations

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

Fields of papers citing papers by Yu Guan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Guan

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Guan. A scholar is included among the top collaborators of Yu Guan 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 Yu Guan. Yu Guan 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
1.
Rehborn, Hubert, et al.. (2025). Crash localization and traffic impact assessment via spatio-temporal analysis of connected vehicle data. Accident Analysis & Prevention. 214. 107956–107956. 1 indexed citations
2.
Guan, Yu, et al.. (2025). Effectiveness of interventions to improve frailty among community-dwelled older adults: A systematic review. Archives of Gerontology and Geriatrics. 137. 105946–105946. 1 indexed citations
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Ma, Yanqing, Bing Fan, Yu Guan, et al.. (2024). CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD. Military Medical Research. 11(1). 14–14. 12 indexed citations
6.
Lian, Yanqing, Qingyun Duan, Zhu Liu, et al.. (2024). Coupled hydrologic and hydraulic modeling for a lowland river basin in China. Journal of Hydrology. 649. 132470–132470. 2 indexed citations
7.
Guan, Yu, Xiaoqing Lin, Liang Mao, et al.. (2024). CT-based whole lung radiomics nomogram for identification of PRISm from non-COPD subjects. Respiratory Research. 25(1). 329–329. 2 indexed citations
8.
Guan, Yu, et al.. (2024). Dynamic characteristics of expectations of short-term interest rate and a generalized Vasicek model. Heliyon. 10(9). e30206–e30206. 1 indexed citations
9.
Zhang, Di, Yu Guan, Weidong Zhang, et al.. (2023). Development of machine learning model to predict pulmonary function with low‐dose CT‐derived parameter response mapping in a community‐based chest screening cohort. Journal of Applied Clinical Medical Physics. 24(11). e14171–e14171. 1 indexed citations
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Rehman, Rana Zia Ur, Yu Guan, Jian Qing Shi, et al.. (2022). Investigating the Impact of Environment and Data Aggregation by Walking Bout Duration on Parkinson’s Disease Classification Using Machine Learning. Frontiers in Aging Neuroscience. 14. 808518–808518. 11 indexed citations
12.
Qian, Bin, Jie Su, Zhenyu Wen, et al.. (2020). Orchestrating the Development Lifecycle of Machine Learning-based IoT Applications. ACM Computing Surveys. 53(4). 1–47. 108 indexed citations
13.
Fan, Li, Yi Xiao, Chenguang Wang, et al.. (2020). Transformation of workflow facing the COVID-19 in the Department of Radiology. Zhonghua fangshexian yixue zazhi. 54(5). 2 indexed citations
14.
Qian, Bin, Jie Su, Zhenyu Wen, et al.. (2019). Orchestrating Development Lifecycle of Machine Learning Based IoT Applications: A Survey.. arXiv (Cornell University). 1 indexed citations
15.
Wang, Junyan, et al.. (2019). Order Matters: Shuffling Sequence Generation for Video Prediction. Durham Research Online (Durham University). 275.
16.
Tu, Wenting, Guangyuan Sun, Li Fan, et al.. (2019). Radiomics signature: A potential and incremental predictor for EGFR mutation status in NSCLC patients, comparison with CT morphology. Lung Cancer. 132. 28–35. 118 indexed citations
17.
Rehman, Rana Zia Ur, Silvia Del Din, Yu Guan, et al.. (2019). Selecting Clinically Relevant Gait Characteristics for Classification of Early Parkinson’s Disease: A Comprehensive Machine Learning Approach. Scientific Reports. 9(1). 17269–17269. 103 indexed citations
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Guan, Yu. (2010). Research on Communication and Networking Technologies of Link16 Data Link.
20.
Guan, Yu. (2000). On conditioned probability matrix and channel theory and Marcov chains. 17(4). 430–435. 1 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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