Mingyue Shang

46 total papers · 526 total citations
23 papers, 260 citations indexed

About

Mingyue Shang is a scholar working on Artificial Intelligence, Surgery and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mingyue Shang has authored 23 papers receiving a total of 260 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 6 papers in Surgery and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mingyue Shang's work include Topic Modeling (11 papers), Natural Language Processing Techniques (10 papers) and Bariatric Surgery and Outcomes (6 papers). Mingyue Shang is often cited by papers focused on Topic Modeling (11 papers), Natural Language Processing Techniques (10 papers) and Bariatric Surgery and Outcomes (6 papers). Mingyue Shang collaborates with scholars based in China, United States and Myanmar. Mingyue Shang's co-authors include Rui Yan, Dongyan Zhao, Shen Gao, Wei Wu, Chongyang Tao, Zhenxin Fu, Lidong Bing, Baishakhi Ray, Siddhartha Jain and Shuming Shi and has published in prestigious journals such as International Journal of Psychophysiology, Obesity Surgery and Surgery for Obesity and Related Diseases.

In The Last Decade

Mingyue Shang

18 papers receiving 250 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Mingyue Shang 185 45 42 27 20 23 260
Parminder Bhatia 194 1.0× 38 0.8× 18 0.4× 18 0.7× 14 0.7× 28 231
Amir Kantor 177 1.0× 47 1.0× 38 0.9× 11 0.4× 21 1.1× 14 232
Dibya Jyoti Bora 70 0.4× 35 0.8× 64 1.5× 8 0.3× 14 0.7× 23 198
Jiajun Shen 177 1.0× 34 0.8× 178 4.2× 15 0.6× 25 1.3× 21 316
Krishna Subramanian 104 0.6× 24 0.5× 114 2.7× 19 0.7× 35 1.8× 26 242
Yu Wang 113 0.6× 88 2.0× 28 0.7× 52 1.9× 29 1.4× 21 220
Florent Jacquemard 142 0.8× 41 0.9× 14 0.3× 12 0.4× 68 3.4× 28 329
Lalita Bhanu Murthy Neti 219 1.2× 114 2.5× 12 0.3× 61 2.3× 34 1.7× 21 321
Pau Giner 108 0.6× 129 2.9× 42 1.0× 19 0.7× 83 4.2× 18 198
Burcu Can 186 1.0× 44 1.0× 24 0.6× 6 0.2× 10 0.5× 38 242

Countries citing papers authored by Mingyue Shang

Since Specialization
Citations

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

Fields of papers citing papers by Mingyue Shang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingyue Shang

This figure shows the co-authorship network connecting the top 25 collaborators of Mingyue Shang. A scholar is included among the top collaborators of Mingyue Shang 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 Mingyue Shang. Mingyue Shang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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