Peishan Dai

679 total citations
34 papers, 469 citations indexed

About

Peishan Dai is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Peishan Dai has authored 34 papers receiving a total of 469 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Radiology, Nuclear Medicine and Imaging, 13 papers in Cognitive Neuroscience and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Peishan Dai's work include Functional Brain Connectivity Studies (12 papers), Glaucoma and retinal disorders (7 papers) and Advanced MRI Techniques and Applications (6 papers). Peishan Dai is often cited by papers focused on Functional Brain Connectivity Studies (12 papers), Glaucoma and retinal disorders (7 papers) and Advanced MRI Techniques and Applications (6 papers). Peishan Dai collaborates with scholars based in China, United States and Singapore. Peishan Dai's co-authors include Zailiang Chen, Miao Liao, Beiji Zou, Hailan Shen, Jing Wu, Xiaohong Wang, Yuqian Zhao, Yuqian Zhao, Xiaoyan Zhou and Junkai Zhang and has published in prestigious journals such as PLoS ONE, Journal of Affective Disorders and Human Brain Mapping.

In The Last Decade

Peishan Dai

30 papers receiving 457 citations

Peers

Peishan Dai
Zailiang Chen China
Cheng‐Kai Lu Malaysia
Neelam Sinha India
Antonios Perperidis United Kingdom
Donghuan Lu China
Robert Splinter United States
Sajid Gul Khawaja Pakistan
Charturong Tantibundhit Thailand
Vincent Nourrit France
Zailiang Chen China
Peishan Dai
Citations per year, relative to Peishan Dai Peishan Dai (= 1×) peers Zailiang Chen

Countries citing papers authored by Peishan Dai

Since Specialization
Citations

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

Fields of papers citing papers by Peishan Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peishan Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Peishan Dai. A scholar is included among the top collaborators of Peishan Dai 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 Peishan Dai. Peishan Dai 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.
Dai, Peishan, et al.. (2025). Altered effective connectivity in patients with drug-naïve first-episode, recurrent, and medicated major depressive disorder: A multi-site fMRI study. Behavioural Brain Research. 495. 115756–115756. 1 indexed citations
2.
Dai, Peishan, et al.. (2025). Estimating brain effective connectivity from time series using recurrent neural networks. Physical and Engineering Sciences in Medicine. 48(2). 785–795.
3.
Dai, Peishan, et al.. (2025). Using effective connectivity-based predictive modeling to predict MDD scale scores from multisite rs-fMRI data. Journal of Neuroscience Methods. 417. 110406–110406. 1 indexed citations
4.
5.
Dai, Peishan, Yun Q. Shi, Ying Zhou, et al.. (2024). Classification of recurrent major depressive disorder using a residual denoising autoencoder framework: Insights from large-scale multisite fMRI data. Computer Methods and Programs in Biomedicine. 247. 108114–108114. 5 indexed citations
6.
Dai, Peishan, et al.. (2024). Deep learning models for ischemic stroke lesion segmentation in medical images: A survey. Computers in Biology and Medicine. 175. 108509–108509. 17 indexed citations
7.
Dai, Peishan, et al.. (2024). Unsupervised generative model for simulating post-operative double eyelid image. Physical and Engineering Sciences in Medicine. 48(1). 49–58.
8.
Shen, Hailan, et al.. (2023). Semi-supervised OCT lesion segmentation via transformation-consistent with uncertainty and self-deep supervision. Biomedical Optics Express. 14(7). 3828–3828. 2 indexed citations
9.
Dai, Peishan, Yun Q. Shi, Ying Zhou, et al.. (2023). Classification of recurrent major depressive disorder using a new time series feature extraction method through multisite rs-fMRI data. Journal of Affective Disorders. 339. 511–519. 14 indexed citations
10.
Li, Yang, Beiji Zou, Peishan Dai, et al.. (2023). AC-E Network: Attentive Context-Enhanced Network for Liver Segmentation. IEEE Journal of Biomedical and Health Informatics. 27(8). 4052–4061. 9 indexed citations
11.
Dai, Peishan, Ying Zhou, Yun Q. Shi, et al.. (2023). Classification of MDD using a Transformer classifier with large‐scale multisite resting‐state fMRI data. Human Brain Mapping. 45(1). e26542–e26542. 18 indexed citations
12.
Dai, Peishan, et al.. (2022). A strategy of model space search for dynamic causal modeling in task fMRI data exploratory analysis. Physical and Engineering Sciences in Medicine. 45(3). 867–882. 3 indexed citations
13.
Dai, Peishan, Xiaoyan Zhou, Yang Li, et al.. (2022). The alterations of brain functional connectivity networks in major depressive disorder detected by machine learning through multisite rs-fMRI data. Behavioural Brain Research. 435. 114058–114058. 21 indexed citations
14.
15.
Hsu, Ting‐Yu, Peishan Dai, & Shiang‐Jung Wang. (2021). Numerical study on smart sloped rolling-type seismic isolators integrated with early prediction of peak velocity. Engineering Structures. 246. 113032–113032. 4 indexed citations
16.
Dai, Peishan, Xiaoyan Zhou, Jinlong Zhang, et al.. (2021). Altered Effective Connectivity of Children and Young Adults With Unilateral Amblyopia: A Resting-State Functional Magnetic Resonance Imaging Study. Frontiers in Neuroscience. 15. 12 indexed citations
17.
Dai, Peishan, et al.. (2016). Retinal Fundus Image Enhancement Using the Normalized Convolution and Noise Removing. International Journal of Biomedical Imaging. 2016. 1–12. 47 indexed citations
18.
Dai, Peishan, et al.. (2016). SIMULATING THE EFFECTS OF ELEVATED INTRAOCULAR PRESSURE ON OCULAR STRUCTURES USING A GLOBAL FINITE ELEMENT MODEL OF THE HUMAN EYE. Journal of Mechanics in Medicine and Biology. 17(2). 1750038–1750038. 7 indexed citations
19.
Dai, Peishan, et al.. (2015). Constructing three-dimensional detachable and composable computer models of the head and neck. Australasian Physical & Engineering Sciences in Medicine. 38(2). 271–281. 1 indexed citations
20.
Dai, Peishan, et al.. (2010). Constructing a Computer Model of the Human Eye Based on Tissue Slice Images. International Journal of Biomedical Imaging. 2010(1). 921469–921469. 5 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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