Yunsong Peng

540 citations
38 papers · 322 indexed · h-index 11
Topics
Radiomics and Machine Learning in Medical Imaging (14 papers)AI in cancer detection (9 papers)Brain Tumor Detection and Classification (6 papers)
Partner nations
ChinaJapanUnited States

In The Last Decade

Yunsong Peng

30 papers receiving 319 citations

Peers

Yunsong Peng
Comparison fields: 5 of 64
  • Radiology, Nuclear Medicine and Imaging 201
  • Artificial Intelligence 133
  • Pulmonary and Respiratory Medicine 61
  • Biomedical Engineering 50
  • Neurology 47
Replace Yohannes Tsehay with:
Yohannes Tsehay United States
Amer Alaref Canada
Rikke Rass Winkel Denmark
Jeremy Webb United States
Hugo Duarte Portugal
Zhaoshuo Diao China
Subrata Bhattacharjee South Korea
Riqiang Gao United States
Yassir Edrees Almalki Saudi Arabia
Zhuo He China
Yunsong Peng relative to Yohannes Tsehay United States Yohannes Tsehay's profile →
Citations per field
00.5×
Yohannes Tsehay · 1×
Citations per year

Countries citing papers authored by Yunsong Peng

Since Specialization
Citations

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

Fields of papers citing papers by Yunsong Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yunsong Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Yunsong Peng. A scholar is included among the top collaborators of Yunsong Peng 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 Yunsong Peng. Yunsong Peng 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
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11 15
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14 30
15 9
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In-plane permeability characterization of fiber fabric based on digital image technology
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20 12

About Yunsong Peng

Yunsong Peng is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Artificial Intelligence, having authored 38 papers that have together received 322 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (14 papers), AI in cancer detection (9 papers) and Brain Tumor Detection and Classification (6 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (201 citations), Health Informatics (10 citations) and Neurology (47 citations). Yunsong Peng has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Jian Zheng, Xiaodong Yang, Lijuan Zhou, Qian Zhang, Wei Liu, Rongpin Wang, Zhuangzhi Yan, Gang Yuan, Xiaodong Yang and Shuangqing Chen. Their work appears in journals such as NeuroImage, Expert Systems with Applications and Life Sciences.

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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