Yongkai Liu

638 total citations
21 papers, 447 citations indexed

About

Yongkai Liu is a scholar working on Pulmonary and Respiratory Medicine, Biomedical Engineering and Epidemiology. According to data from OpenAlex, Yongkai Liu has authored 21 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Pulmonary and Respiratory Medicine, 7 papers in Biomedical Engineering and 6 papers in Epidemiology. Recurrent topics in Yongkai Liu's work include Prostate Cancer Diagnosis and Treatment (7 papers), Acute Ischemic Stroke Management (6 papers) and Cerebrovascular and Carotid Artery Diseases (5 papers). Yongkai Liu is often cited by papers focused on Prostate Cancer Diagnosis and Treatment (7 papers), Acute Ischemic Stroke Management (6 papers) and Cerebrovascular and Carotid Artery Diseases (5 papers). Yongkai Liu collaborates with scholars based in United States, China and United Kingdom. Yongkai Liu's co-authors include Guang Yang, Kyunghyun Sung, Steven S. Raman, Xiaobo Lai, Xiaomei Xu, Sohrab Afshari Mirak, Melina Hosseiny, Qi Miao, He Huang and W. Yang and has published in prestigious journals such as Stroke, Scientific Reports and Radiology.

In The Last Decade

Yongkai Liu

18 papers receiving 437 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yongkai Liu United States 9 228 170 160 131 104 21 447
Anup Sadhu India 12 127 0.6× 64 0.4× 209 1.3× 123 0.9× 154 1.5× 40 404
Ying Fang China 13 116 0.5× 69 0.4× 266 1.7× 50 0.4× 52 0.5× 54 487
Audrey H. Zhuang United States 6 212 0.9× 97 0.6× 197 1.2× 94 0.7× 46 0.4× 8 443
Jhimli Mitra France 9 260 1.1× 67 0.4× 134 0.8× 119 0.9× 74 0.7× 18 434
Palash Ghosal India 9 171 0.8× 168 1.0× 89 0.6× 24 0.2× 91 0.9× 21 315
Jiancong Wang United States 12 157 0.7× 75 0.4× 175 1.1× 23 0.2× 97 0.9× 24 414
Tianyu Shi China 9 168 0.7× 89 0.5× 207 1.3× 37 0.3× 153 1.5× 16 405
Tabea Kossen Germany 8 137 0.6× 55 0.3× 119 0.7× 73 0.6× 62 0.6× 12 310
Lucas Fidon United Kingdom 6 138 0.6× 60 0.4× 216 1.4× 45 0.3× 131 1.3× 13 447
Ahmed Alksas United States 10 67 0.3× 49 0.3× 211 1.3× 72 0.5× 73 0.7× 40 330

Countries citing papers authored by Yongkai Liu

Since Specialization
Citations

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

Fields of papers citing papers by Yongkai Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yongkai Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Yongkai Liu. A scholar is included among the top collaborators of Yongkai Liu 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 Yongkai Liu. Yongkai Liu 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.
Jiang, Bin, Yongkai Liu, Amirhossein Sanaat, et al.. (2025). Deep Learning Applications in Imaging of Acute Ischemic Stroke: A Systematic Review and Narrative Summary. Radiology. 315(1). e240775–e240775.
2.
3.
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
4.
Liu, Yongkai, Preya Shah, Yannan Yu, et al.. (2024). A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes. American Journal of Neuroradiology. 45(4). 406–411. 4 indexed citations
5.
6.
Verhaaren, Benjamin F.J., Søren Christensen, Abdelkader Mahammedi, et al.. (2023). Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists. Scientific Reports. 13(1). 16153–16153. 6 indexed citations
7.
Liu, Yongkai, Yannan Yu, Jiahong Ouyang, et al.. (2023). Functional Outcome Prediction in Acute Ischemic Stroke Using a Fused Imaging and Clinical Deep Learning Model. Stroke. 54(9). 2316–2327. 26 indexed citations
8.
9.
Wu, Holden H., Yongkai Liu, Dominik Nickel, et al.. (2022). Undersampling artifact reduction for free-breathing 3D stack-of-radial MRI based on a deep adversarial learning network. Magnetic Resonance Imaging. 95. 70–79. 3 indexed citations
10.
Miao, Qi, Yongkai Liu, Sohrab Afshari Mirak, et al.. (2022). Multiparametric MRI-based radiomics model to predict pelvic lymph node invasion for patients with prostate cancer. European Radiology. 32(8). 5688–5699. 33 indexed citations
11.
Liu, Yongkai, Fatemeh Zabihollahy, Ran Yan, et al.. (2022). Evaluation of Spatial Attentive Deep Learning for Automatic Placental Segmentation on Longitudinal MRI. Journal of Magnetic Resonance Imaging. 57(5). 1533–1540. 9 indexed citations
12.
Liu, Yongkai, Qi Miao, Dan Nguyen, et al.. (2021). Deep Learning Enables Prostate MRI Segmentation: A Large Cohort Evaluation With Inter-Rater Variability Analysis. Frontiers in Oncology. 11. 801876–801876. 7 indexed citations
13.
Zhang, Wenbo, Guang Yang, He Huang, et al.. (2021). ME‐Net: Multi‐encoder net framework for brain tumor segmentation. International Journal of Imaging Systems and Technology. 31(4). 1834–1848. 100 indexed citations
14.
Liu, Yongkai, Zhengrong Liang, Qi Miao, et al.. (2021). Textured-Based Deep Learning in Prostate Cancer Classification with 3T Multiparametric MRI: Comparison with PI-RADS-Based Classification. Diagnostics. 11(10). 1785–1785. 21 indexed citations
15.
Miao, Qi, et al.. (2021). Integrative Machine Learning Prediction of Prostate Biopsy Results From Negative Multiparametric MRI. Journal of Magnetic Resonance Imaging. 55(1). 100–110. 13 indexed citations
16.
Yang, Guang, Ying Fang, Ruipeng Li, et al.. (2020). 3D PBV-Net: An automated prostate MRI data segmentation method. Computers in Biology and Medicine. 128. 104160–104160. 71 indexed citations
17.
Liu, Yongkai, Guang Yang, Melina Hosseiny, et al.. (2020). Exploring Uncertainty Measures in Bayesian Deep Attentive Neural Networks for Prostate Zonal Segmentation. IEEE Access. 8. 151817–151828. 65 indexed citations
18.
Liu, Yongkai, Kyunghyun Sung, Guang Yang, et al.. (2019). Automatic Prostate Zonal Segmentation Using Fully Convolutional Network With Feature Pyramid Attention. IEEE Access. 7. 163626–163632. 75 indexed citations
19.
Liu, Yongkai, et al.. (2016). Haustral loop extraction for CT colonography using geodesics. International Journal of Computer Assisted Radiology and Surgery. 12(3). 379–388. 4 indexed citations
20.
Zhang, Shoucheng & Yongkai Liu. (2012). Fixed-point algorithm based on kurtosis for one-unit ICA-R. 48(2). 130–132. 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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