Shan Yang

2.5k citations
43 papers · 1.1k indexed · 3 hit papers · h-index 12
Topics
Radiomics and Machine Learning in Medical Imaging (10 papers)Advanced MIMO Systems Optimization (8 papers)Cardiac Imaging and Diagnostics (5 papers)

In The Last Decade

Shan Yang

40 papers receiving 1.1k citations

Hit Papers

TotalSegmentator: Robust Segmentation of 104 Anatomi...2021202620222024202320212025100200300400

Peers

Shan Yang
Comparison fields: 5 of 103
  • Radiology, Nuclear Medicine and Imaging 466
  • Computer Vision and Pattern Recognition 331
  • Biomedical Engineering 227
  • Control and Systems Engineering 194
  • Artificial Intelligence 151
Replace Matthew Field with:
Matthew Field Australia
Hélder P. Oliveira Portugal
Hong Song China
Martin Lillholm Denmark
Yongwon Cho South Korea
Angelica I. Avilés-Rivero United Kingdom
Fatma Taher United Arab Emirates
Floris Ernst Germany
Zhifan Gao China
Alexander Schlaefer Germany
Shan Yang relative to Matthew Field Australia Matthew Field's profile →
Citations per field
00.5×5.1×
Matthew Field · 1×
Citations per year

Countries citing papers authored by Shan Yang

Since Specialization
Citations

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

Fields of papers citing papers by Shan Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shan Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Shan Yang. A scholar is included among the top collaborators of Shan Yang 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 Shan Yang. Shan Yang 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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TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRIbreakdown →
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3 1
4 0
5 4
6 11
7 23
8 8
9 4
10 14
11 11
12 29
13 19
14 1
15 10
16 18
17 38
18 14
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Interference modeling and performance evaluation for BS MMSE-IRC receiver in LTE-A release 13
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Study on three level system population transfer
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About Shan Yang

Shan Yang is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Computer Networks and Communications, having authored 43 papers that have together received 1.1k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), Advanced MIMO Systems Optimization (8 papers) and Cardiac Imaging and Diagnostics (5 papers). The work is most often cited by research in Health Informatics (66 citations), Radiology, Nuclear Medicine and Imaging (466 citations) and Computer Vision and Pattern Recognition (331 citations). Shan Yang has collaborated with scholars based in Switzerland, China and United States. Frequent co-authors include David A. Ross, Angjoo Kanazawa, Ruilong Li, Alexander Sauter, Joshy Cyriac, Jakob Wasserthal, Michael Bach, Daniel T. Boll, Martin Segeroth and Hanns‐Christian Breit. Their work appears in journals such as PLoS ONE, Radiology and Cells.

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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