Yannan Yu

998 total citations
42 papers, 599 citations indexed

About

Yannan Yu is a scholar working on Epidemiology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Yannan Yu has authored 42 papers receiving a total of 599 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Epidemiology, 23 papers in Pulmonary and Respiratory Medicine and 12 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Yannan Yu's work include Acute Ischemic Stroke Management (28 papers), Cerebrovascular and Carotid Artery Diseases (23 papers) and Advanced MRI Techniques and Applications (7 papers). Yannan Yu is often cited by papers focused on Acute Ischemic Stroke Management (28 papers), Cerebrovascular and Carotid Artery Diseases (23 papers) and Advanced MRI Techniques and Applications (7 papers). Yannan Yu collaborates with scholars based in United States, China and Australia. Yannan Yu's co-authors include Min Lou, Greg Zaharchuk, David S. Liebeskind, Gregory W. Albers, Maarten G. Lansberg, Fabien Scalzo, Jiahong Ouyang, Sören Christensen, Yuan Xie and Enhao Gong and has published in prestigious journals such as Neurology, Stroke and Scientific Reports.

In The Last Decade

Yannan Yu

38 papers receiving 593 citations

Peers

Yannan Yu
Lucas A. Ramos Netherlands
Adam Hilbert Germany
Mohamed Najm Canada
Anna M.M. Boers Netherlands
Philip Hoelter Germany
Gagan Sharma Australia
Kunakorn Atchaneeyasakul United States
Zarina Assis Canada
David Robben Belgium
Edwin Bennink Netherlands
Lucas A. Ramos Netherlands
Yannan Yu
Citations per year, relative to Yannan Yu Yannan Yu (= 1×) peers Lucas A. Ramos

Countries citing papers authored by Yannan Yu

Since Specialization
Citations

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

Fields of papers citing papers by Yannan Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yannan Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Yannan Yu. A scholar is included among the top collaborators of Yannan 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 Yannan Yu. Yannan 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
1.
Yu, Xinfeng, Duo Xu, Yannan Yu, et al.. (2025). Chronic cerebral hypoperfusion‐induced myelin loss in normal‐appearing white matter correlates with cognitive decline: insights from moyamoya disease. Alzheimer s & Dementia Translational Research & Clinical Interventions. 11(4). e70164–e70164.
2.
Yu, Yannan, et al.. (2025). Correlation Between 4DCT Enhancement Patterns and Parathyroid Adenoma Cellularity: A Retrospective Study. American Journal of Neuroradiology. ajnr.A9090–ajnr.A9090.
3.
Du, Wenliao, et al.. (2025). Multi-scale wavelet decomposition and feature fusion for rotating machinery fault diagnosis under multi-level class imbalance. Mechanical Systems and Signal Processing. 240. 113427–113427. 2 indexed citations
4.
Du, Wenliao, et al.. (2024). Few-shot sample multi-class incremental fault diagnosis for gearbox based on convolutional-attention fusion network. Expert Systems with Applications. 264. 125918–125918. 12 indexed citations
5.
Liu, Yongkai, Yannan Yu, Jiahong Ouyang, et al.. (2024). Prediction of Ischemic Stroke Functional Outcomes from Acute-Phase Noncontrast CT and Clinical Information. Radiology. 313(1). e240137–e240137. 3 indexed citations
6.
Yu, Xinfeng, et al.. (2024). Exploring the Impact of Hemoglobin on Cerebral Blood Flow in Arterial Territories and Surgical Outcomes: Potential Implications for Moyamoya Disease Treatment. Journal of the American Heart Association. 13(19). e035387–e035387. 3 indexed citations
7.
Chen, Jian, et al.. (2023). Is manufacturing trade a stepping stone or an obstacle to service trade?. International Journal of Emerging Markets. 20(2). 767–786.
8.
Yu, Yannan, Maarten G. Lansberg, David S. Liebeskind, et al.. (2022). Predicting final ischemic stroke lesions from initial diffusion-weighted images using a deep neural network. NeuroImage Clinical. 37. 103278–103278. 19 indexed citations
9.
Yu, Yannan, Sören Christensen, Jiahong Ouyang, et al.. (2022). Predicting Hypoperfusion Lesion and Target Mismatch in Stroke from Diffusion-weighted MRI Using Deep Learning. Radiology. 307(1). e220882–e220882. 19 indexed citations
10.
Yu, Yannan, Yuan Xie, Enhao Gong, et al.. (2021). Tissue at Risk and Ischemic Core Estimation Using Deep Learning in Acute Stroke. American Journal of Neuroradiology. 42(6). 1030–1037. 24 indexed citations
11.
Zhang, Xuting, Shenqiang Yan, Wansi Zhong, Yannan Yu, & Min Lou. (2021). Early NT-ProBNP (N-Terminal Probrain Natriuretic Peptide) Elevation Predicts Malignant Edema and Death After Reperfusion Therapy in Acute Ischemic Stroke Patients. Stroke. 52(2). 537–542. 19 indexed citations
12.
Yu, Yannan, Jeremy J. Heit, & Greg Zaharchuk. (2021). Improving Ischemic Stroke Care With MRI and Deep Learning Artificial Intelligence. Topics in Magnetic Resonance Imaging. 30(4). 187–195. 14 indexed citations
13.
Chen, Yu‐Wen, Jia Liu, Mingli Li, et al.. (2021). Non-invasive assessment of intracranial wall shear stress using high-resolution magnetic resonance imaging in combination with computational fluid dynamics technique. Fundamental Research. 2(2). 329–334. 9 indexed citations
14.
15.
Yu, Yannan, et al.. (2020). Perfusion Parameter Thresholds That Discriminate Ischemic Core Vary with Time from Onset in Acute Ischemic Stroke. American Journal of Neuroradiology. 41(10). 1809–1815. 7 indexed citations
16.
Zhang, Sheng, Longting Lin, Ruiting Zhang, et al.. (2020). Absent Contrast Filling of Ipsilateral Superficial Middle Cerebral Vein Predicts Midline Shift in Acute Middle Cerebral Artery Occlusion. Frontiers in Neurology. 11. 570844–570844. 6 indexed citations
17.
Zhang, Sheng, Ruiting Zhang, Bo Jin, et al.. (2020). Absent filling of the superficial middle cerebral vein is associated with reperfusion but not parenchymal hematoma in stroke patients undergoing thrombectomy: an observational study. Annals of Translational Medicine. 8(21). 1410–1410. 7 indexed citations
18.
Li, Mingli, Yannan Yu, Yuyuan Xu, et al.. (2019). Quantitative score of the vessel morphology in middle cerebral artery atherosclerosis. Journal of the Neurological Sciences. 399. 111–117. 8 indexed citations
19.
Yu, Yannan, Danfeng Guo, Min Lou, David S. Liebeskind, & Fabien Scalzo. (2018). The Prediction of The Hemorrhagic Transformation Locations After Reperfusion Therapy in Acute Stroke Patients: A Perfusion Study using Deep Learning (P3.212). Neurology. 90(15_supplement). 2 indexed citations
20.
Zhang, Sheng, Huan Tang, Yannan Yu, et al.. (2014). Optimal Magnetic Resonance Perfusion Thresholds Identifying Ischemic Penumbra and Infarct Core: A Chinese Population‐based Study. CNS Neuroscience & Therapeutics. 21(3). 289–295. 13 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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