Po-Shan Wang

538 total citations
27 papers, 427 citations indexed

About

Po-Shan Wang is a scholar working on Cellular and Molecular Neuroscience, Neurology and Cognitive Neuroscience. According to data from OpenAlex, Po-Shan Wang has authored 27 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cellular and Molecular Neuroscience, 12 papers in Neurology and 11 papers in Cognitive Neuroscience. Recurrent topics in Po-Shan Wang's work include Genetic Neurodegenerative Diseases (13 papers), Advanced Neuroimaging Techniques and Applications (11 papers) and Functional Brain Connectivity Studies (8 papers). Po-Shan Wang is often cited by papers focused on Genetic Neurodegenerative Diseases (13 papers), Advanced Neuroimaging Techniques and Applications (11 papers) and Functional Brain Connectivity Studies (8 papers). Po-Shan Wang collaborates with scholars based in Taiwan, United States and United Kingdom. Po-Shan Wang's co-authors include Bing‐Wen Soong, Yu‐Te Wu, Hsiu‐Mei Wu, Kuo‐Kai Shyu, Jiing-Feng Lirng, Yi‐Chung Lee, Ren-Shyan Liu, Hsiu-Chih Liu, Yi‐Chu Liao and Chia‐Feng Lu and has published in prestigious journals such as PLoS ONE, NeuroImage and Sensors.

In The Last Decade

Po-Shan Wang

26 papers receiving 415 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Po-Shan Wang Taiwan 12 167 139 132 118 116 27 427
A. Colleluori Italy 5 119 0.7× 113 0.8× 103 0.8× 82 0.7× 101 0.9× 5 377
Yoko Shigemoto Japan 13 139 0.8× 87 0.6× 188 1.4× 63 0.5× 112 1.0× 54 465
Carlos A. Sánchez-Catasús Netherlands 12 84 0.5× 121 0.9× 122 0.9× 49 0.4× 109 0.9× 32 391
Alexander Dubrovsky Russia 10 156 0.9× 60 0.4× 94 0.7× 63 0.5× 47 0.4× 20 334
Jeroen J. de Vries Netherlands 10 164 1.0× 192 1.4× 72 0.5× 138 1.2× 73 0.6× 16 587
Tim Buchanan Belgium 11 181 1.1× 170 1.2× 90 0.7× 111 0.9× 146 1.3× 15 659
L. I. Wallis United Kingdom 9 84 0.5× 220 1.6× 123 0.9× 67 0.6× 34 0.3× 13 410
Sebastian Brandner Germany 11 105 0.6× 155 1.1× 61 0.5× 89 0.8× 32 0.3× 46 434
Xuan Vinh To Australia 9 126 0.8× 122 0.9× 115 0.9× 116 1.0× 68 0.6× 31 378
Jean‐Philippe Coutu United States 9 69 0.4× 58 0.4× 200 1.5× 58 0.5× 87 0.8× 12 374

Countries citing papers authored by Po-Shan Wang

Since Specialization
Citations

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

Fields of papers citing papers by Po-Shan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Po-Shan Wang. 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 Po-Shan Wang. The network helps show where Po-Shan Wang may publish in the future.

Co-authorship network of co-authors of Po-Shan Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Po-Shan Wang. A scholar is included among the top collaborators of Po-Shan Wang 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 Po-Shan Wang. Po-Shan Wang 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.
Wu, Hsiu‐Mei, et al.. (2024). Morphological changes of cerebral gray matter in spinocerebellar ataxia type 3 using fractal dimension analysis. Progress in brain research. 290. 1–21.
2.
Wu, Chih‐Chun, Cheng‐Chia Lee, Chia‐Feng Lu, et al.. (2020). Combining analysis of multi-parametric MR images into a convolutional neural network: Precise target delineation for vestibular schwannoma treatment planning. Artificial Intelligence in Medicine. 107. 101911–101911. 26 indexed citations
3.
Wang, Po-Shan, et al.. (2020). Supratentorial and Infratentorial Lesions in Spinocerebellar Ataxia Type 3. Frontiers in Neurology. 11. 124–124. 8 indexed citations
4.
Wu, Yu‐Te, et al.. (2020). Alteration of the Intra- and Inter-Lobe Connectivity of the Brain Structural Network in Normal Aging. Entropy. 22(8). 826–826. 6 indexed citations
5.
Soong, Bing‐Wen, et al.. (2019). Diffusion Tensor Magnetic Resonance Imaging for Differentiating Multiple System Atrophy Cerebellar Type and Spinocerebellar Ataxia Type 3. Brain Sciences. 9(12). 354–354. 14 indexed citations
6.
Liu, Yo-Tsen, Hsiang‐Yu Yu, Kwong-Kum Liao, et al.. (2018). Aberrant Sensory Gating of the Primary Somatosensory Cortex Contributes to the Motor Circuit Dysfunction in Paroxysmal Kinesigenic Dyskinesia. Frontiers in Neurology. 9. 831–831. 9 indexed citations
7.
Wu, Yu-Te, et al.. (2018). Impaired Efficiency and Resilience of Structural Network in Spinocerebellar Ataxia Type 3. Frontiers in Neuroscience. 12. 935–935. 7 indexed citations
8.
Wang, Po-Shan, et al.. (2016). The involvement of supratentorial white matter in multiple system atrophy: a diffusion tensor imaging tractography study. Acta Neurologica Belgica. 117(1). 213–220. 16 indexed citations
9.
Wu, Yu-Te, et al.. (2016). CAG repeat length does not associate with the rate of cerebellar degeneration in spinocerebellar ataxia type 3. NeuroImage Clinical. 13. 97–105. 22 indexed citations
10.
Wang, Tzu‐Yun, Bing‐Wen Soong, Hsiu‐Mei Wu, et al.. (2015). Change in the Cortical Complexity of Spinocerebellar Ataxia Type 3 Appears Earlier than Clinical Symptoms. PLoS ONE. 10(4). e0118828–e0118828. 15 indexed citations
11.
Wang, Po-Shan, et al.. (2013). Cortical Shape and Curvedness Analysis of Structural Deficits in Remitting and Non-Remitting Depression. PLoS ONE. 8(7). e68625–e68625. 7 indexed citations
12.
Lai, Tzu-Hsien, Ren-Shyan Liu, Bang‐Hung Yang, et al.. (2013). Cerebral involvement in spinal and bulbar muscular atrophy (Kennedy's disease): A pilot study of PET. Journal of the Neurological Sciences. 335(1-2). 139–144. 24 indexed citations
13.
Wu, Yu‐Te, Kuo‐Kai Shyu, Tzu‐Yun Wang, et al.. (2012). Quantifying cerebellar atrophy in multiple system atrophy of the cerebellar type (MSA-C) using three-dimensional gyrification index analysis. NeuroImage. 61(1). 1–9. 11 indexed citations
14.
Lirng, Jiing-Feng, et al.. (2012). Differences between Spinocerebellar Ataxias and Multiple System Atrophy-Cerebellar Type on Proton Magnetic Resonance Spectroscopy. PLoS ONE. 7(10). e47925–e47925. 37 indexed citations
15.
16.
17.
Wang, Po-Shan, et al.. (2008). Early Detection of Periodic Sharp Wave Complexes on EEG by Independent Component Analysis in Patients With Creutzfeldt-Jakob Disease. Journal of Clinical Neurophysiology. 25(1). 25–31. 25 indexed citations
18.
Wang, Po-Shan, Ren-Shyan Liu, Bang‐Hung Yang, & Bing‐Wen Soong. (2007). Topographic brain mapping of the international cooperative ataxia rating scale. Journal of Neurology. 254(6). 722–728. 6 indexed citations
19.
Liao, Yi‐Chu, Ren-Shyan Liu, Yi‐Chung Lee, et al.. (2003). Selective Hypoperfusion of Anterior Cingulate Gyrus in Depressed AD Patients: A Brain SPECT Finding by Statistical Parametric Mapping. Dementia and Geriatric Cognitive Disorders. 16(4). 238–244. 39 indexed citations
20.
Lee, Yi‐Chung, Ru‐Shi Liu, Yi‐Chu Liao, et al.. (2003). Statistical Parametric Mapping of Brain SPECT Perfusion Abnormalities in Patients with Alzheimer’s Disease. European Neurology. 49(3). 142–145. 22 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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