Mingyu Chen

6.1k citations
194 papers · 4.3k · 1 hit paper · h-index 35

Impact in

Papers in

Mingyu Chen

175 papers receiving 4.2k citations

Mingyu Chen's Hit Papers

Targeting mutant p53 for cancer therapy: direct and indirect strategies 2021 · 379 citations
3790+1+3Years since publication100200300

Peers

Mingyu Chen
Comparison fields: 5 of 177
  • Human-Computer Interaction 296
  • Computer Vision and Pattern Recognition 737
  • Hepatology 209
  • Cancer Research 344
  • Health Informatics 35
Replace Ming Li with:
Ming Li China
Hye Sun Park South Korea
Xiyang Liu China
Ziyu Liu China
Xiaoyue Wang China
Kenichiro Ishii Japan
Zhicheng Liu China
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Mingyu Chen relative to Ming Li China Ming Li's profile →
Citations per field
00.5×2×4×6×7.4×
Ming Li · 1×
Citations per year

Countries citing papers authored by Mingyu Chen

Since Specialization
Citations

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

Fields of papers citing papers by Mingyu Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mingyu Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mingyu Chen Line = papers co-authored together Mingyu Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 194 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Targeting mutant p53 for cancer therapy: direct and indirect strategies
Hit paper breakdown →
2021379
2 2020189
3 2020187
4 2018160
5 2020134
6 2009134
7 2018125
8 2015121
9 201894
10 202194
11 200690
12 202086
13 202183
14 202381
15 201967
16 202465
17 201965
18 201562
19 202159
20 201759

About Mingyu Chen

Mingyu Chen is a scholar working on Computer Vision and Pattern Recognition, Hepatology, Surgery, Human-Computer Interaction and Oncology, having authored 194 papers that have together received 4.3k indexed citations. Recurring topics across this work include Cholangiocarcinoma and Gallbladder Cancer Studies (14 papers), Advanced Image and Video Retrieval Techniques (14 papers), Human Pose and Action Recognition (14 papers), Video Analysis and Summarization (13 papers), Hepatocellular Carcinoma Treatment and Prognosis (10 papers), Hand Gesture Recognition Systems (9 papers), Nanoplatforms for cancer theranostics (8 papers) and Electrocatalysts for Energy Conversion (7 papers). The work is most often cited by research in Human-Computer Interaction (296 citations), Computer Vision and Pattern Recognition (737 citations), Hepatology (209 citations), Cancer Research (344 citations) and Health Informatics (35 citations). Mingyu Chen has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Xiujun Cai, Sarun Juengpanich, Jiasheng Cao, Alexander G. Hauptmann, Win Topatana, Bin Zhang, Ghassan AlRegib, Biing-Hwang Fred Juang, Jiahao Hu and Shijie Li. Their work appears in journals such as Liver Cancer, Frontiers in Oncology, Journal of Nanobiotechnology, Annals of Translational Medicine and World Journal of Gastroenterology.

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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