Pengchen Liang

486 citations
28 papers · 225 indexed · 1 hit paper · h-index 8
Topics
AI in cancer detection (5 papers)Advanced Neural Network Applications (5 papers)COVID-19 diagnosis using AI (4 papers)
Partner nations
ChinaHong KongSingapore

In The Last Decade

Pengchen Liang

24 papers receiving 221 citations

Hit Papers

H-vmunet: High-order Vision Mamba UNet for medical image ...20252026202510203040

Peers

Pengchen Liang
Comparison fields: 5 of 70
  • Computer Vision and Pattern Recognition 75
  • Artificial Intelligence 59
  • Oncology 53
  • Radiology, Nuclear Medicine and Imaging 35
  • Biomedical Engineering 35
Replace Zhigang Fu with:
Zhigang Fu China
Chengtao Peng China
Andreea-Iuliana Ionescu Romania
Zeshan Hussain United States
Shucheng Cao China
Po-Chi Huang Taiwan
Zhaoyun Cheng China
Sahadev Poudel South Korea
Renkai Wu China
Pengchen Liang relative to Zhigang Fu China Zhigang Fu's profile →
Citations per field
00.5×1.5×2.3×
Zhigang Fu · 1×
Citations per year

Countries citing papers authored by Pengchen Liang

Since Specialization
Citations

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

Fields of papers citing papers by Pengchen Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengchen Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Pengchen Liang. A scholar is included among the top collaborators of Pengchen Liang 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 Pengchen Liang. Pengchen Liang 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
#WorkIndexed citations
1 6
2 0
3 1
4 3
5 0
6 10
7 2
8 1
9 5
10 1
11 5
12 48
13 0
14 4
15 10
16 24
17 3
18 2
19 5
20 11

About Pengchen Liang

Pengchen Liang is a scholar working on Computer Vision and Pattern Recognition, Periodontics and Cancer Research, having authored 28 papers that have together received 225 indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Advanced Neural Network Applications (5 papers) and COVID-19 diagnosis using AI (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (75 citations), Neurology (18 citations) and Oncology (53 citations). Pengchen Liang has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Qing Chang, Renkai Wu, Yinghao Liu, Xuan Huang, Haiqin Zhu, Yuandong Gu, Dongyu Liang, Xiaoxu Cui, Jianguo Chen and Lei Yao. Their work appears in journals such as Scientific Reports, BMC Bioinformatics and BMC Public Health.

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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