Ke Yan

3.3k citations
21 papers · 1.4k indexed · 2 hit papers · h-index 13

Impact in

Papers in

Ke Yan

18 papers receiving 1.4k citations

Hit Papers

Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks 2019 · 439 citations
4392018202620202023100200300400

Peers

Ke Yan
Comparison fields: 5 of 125
  • Health Informatics 78
  • Computer Vision and Pattern Recognition 612
  • Radiology, Nuclear Medicine and Imaging 612
  • Artificial Intelligence 470
  • Media Technology 66
Replace Diana Mateus with:
Diana Mateus France
Jie‐Zhi Cheng China
Ilker Hacihaliloglu United States
Jorge Novo Spain
Veronika Cheplygina Netherlands
Yuting He China
Mehdi Moradi United States
Lin Han China
Xiaohuan Cao China
Ke Yan relative to Diana Mateus France Diana Mateus's profile →
Citations per field
00.5×1.5×
Diana Mateus · 1×
Citations per year

Countries citing papers authored by Ke Yan

Since Specialization
Citations

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

Fields of papers citing papers by Ke Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Ke Yan, 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 Ke Yan Line = papers co-authored together Ke Yan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20252
2 20250
3 20250
4 20246
5 20240
6 20238
7 202222
8 202172
9 202117
10 2020146
11 202043
12
Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks
Hit paper breakdown →
2019439
13 201931
14 201911
15 201925
16 201831
17
DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning
Hit paper breakdown →
2018292
18 201873
19 20171
20 201646

About Ke Yan

Ke Yan is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Health Information Management and Hepatology, having authored 21 papers that have together received 1.4k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), Advanced Neural Network Applications (8 papers), AI in cancer detection (6 papers), COVID-19 diagnosis using AI (5 papers), Advanced Image and Video Retrieval Techniques (4 papers), Video Surveillance and Tracking Methods (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Topic Modeling (2 papers). The work is most often cited by research in Health Informatics (78 citations), Computer Vision and Pattern Recognition (612 citations), Radiology, Nuclear Medicine and Imaging (612 citations), Artificial Intelligence (470 citations) and Media Technology (66 citations). Ke Yan has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Ronald M. Summers, Veit Sandfort, Perry J. Pickhardt, Le Lü, Xiaosong Wang, Youbao Tang, Shijian Lu, Huizhu Jia, Xiaodong Xie and Wen Gao. Their work appears in journals such as IEEE Transactions on Medical Imaging, Scientific Reports, npj Digital Medicine, Computers, materials & continua/Computers, materials & continua (Print) and Medical Image Analysis.

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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