World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
8553
World Ranking
9173
National Ranking
128

Yen-Wei Chen publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Yen-Wei Chen sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 740 publications — 98th percentile

98% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Yen-Wei Chen D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Yen-Wei Chen sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Yen-Wei Chen is affiliated with Ritsumeikan University in Japan and has contributed extensively to research at the intersection of computer science and medicine. Their main fields of study include Computer Science and Medicine, with a particular focus on subfields such as Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Neurology, and Biomedical Engineering.

The scientist's research topics include:

  • Radiomics and Machine Learning in Medical Imaging
  • Advanced Neural Network Applications
  • AI in Cancer Detection
  • Medical Image Segmentation Techniques
  • Brain Tumor Detection and Classification
  • COVID-19 Diagnosis Using AI
  • Advanced Image Processing Techniques

Yen-Wei Chen has co-authored numerous publications with frequent collaborators including Lanfen Lin, Yutaro Iwamoto, Hongjie Hu, Xian-Hua Han, and Ruofeng Tong.

The scientist has published significant work in well-known venues such as:

  • arXiv (Cornell University)
  • IEEE Journal of Biomedical and Health Informatics
  • 2022 IEEE International Conference on Consumer Electronics (ICCE)
  • 2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)
  • Applied Sciences

Some of the recent papers authored or co-authored by Yen-Wei Chen include:

  • Mixed Transformer U-Net for Medical Image Segmentation, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Conservation and Divergence of Vulnerability and Responses to Stressors Between Human and Mouse Astrocytes, 2021, Nature Communications
  • Accuracy of CAD/CAM Digital Impressions with Different Intraoral Scanner Parameters, 2020, Sensors
  • CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression Estimation, 2022, Proceedings of the 30th ACM International Conference on Multimedia
  • Automatic Cephalometric Landmark Detection on X-ray Images Using a Deep-Learning Method, 2020, Applied Sciences

Yen-Wei Chen has also contributed to multiple book publications, predominantly with Springer Nature and Springer International Publishing. Titles include Handbook of Artificial Intelligence in Healthcare (2021), Intelligent System Design (2020, 2022), Artificial Intelligence and Machine Learning for Healthcare (2022), Innovation in Medicine and Healthcare (2020, 2021), Recent Advances in Logo Detection Using Machine Learning Paradigms (2024), and Recent Advances in Deep Learning for Medical Image Analysis (2025).

Best Publications

  • Mixed Transformer U-Net For Medical Image Segmentation.

    Hongyi Wang;Shiao Xie;Lanfen Lin;Yutaro Iwamoto

  • Automated segmentation of the liver from 3D CT images using probabilistic atlas and multilevel statistical shape model.

    Toshiyuki Okada;Ryuji Shimada;Masatoshi Hori;Masahiko Nakamoto

  • Letter: Supervised kernel locality preserving projections for face recognition

    Jian Cheng;Qingshan Liu;Hanqing Lu;Yen-Wei Chen

  • Ensemble learning for independent component analysis

    Jian Cheng;Qingshan Liu;Hanqing Lu;Yen-Wei Chen

  • VesselNet: A deep convolutional neural network with multi pathways for robust hepatic vessel segmentation

    Titinunt Kitrungrotsakul;Xian-Hua Han;Yutaro Iwamoto;Lanfen Lin

  • Medical Image Classification Using Deep Learning

    Weibin Wang;Dong Liang;Qingqing Chen;Yutaro Iwamoto

  • Automatic Cephalometric Landmark Detection on X-ray Images Using a Deep-Learning Method

    Yu Song;Xu Qiao;Yutaro Iwamoto;Yen-wei Chen

  • Automated segmentation of the liver from 3D CT images using probabilistic atlas and multi-level statistical shape model

    Toshiyuki Okada;Ryuji Shimada;Yoshinobu Sato;Masatoshi Hori

  • Robust multi-logo watermarking by RDWT and ICA

    Thai Duy Hien;Zensho Nakao;Yen-Wei Chen

  • Robust Japanese Road Sign Detection and Recognition in Complex Scenes Using Convolutional Neural Networks

    Ryo Hasegawa;Yutaro Iwamoto

  • Multi-Modal Adaptive Fusion Transformer Network for the Estimation of Depression Level.

    Hao Sun;Jiaqing Liu;Shurong Chai;Zhaolin Qiu

  • Semi-supervised Segmentation of Liver Using Adversarial Learning with Deep Atlas Prior

    Han Zheng;Lanfen Lin;Hongjie Hu;Qiaowei Zhang

  • Sparse Codebook Model of Local Structures for Retrieval of Focal Liver Lesions Using Multiphase Medical Images

    Jian Wang;Xian-Hua Han;Yingying Xu;Lanfen Lin

  • Segmentation of Liver in Low-Contrast Images Using K-Means Clustering and Geodesic Active Contour Algorithms

    Amir Hossein Foruzan;Yen-Wei Chen;Reza Aghaeizadeh Zoroofi;Akira Furukawa

  • Improved segmentation of low-contrast lesions using sigmoid edge model

    Amir Hossein Foruzan;Yen-Wei Chen

  • K-CPD: Learning of overcomplete dictionaries for tensor sparse coding

    Guifang Duan;Hongcui Wang;Zhenyu Liu;Junping Deng

  • Combining Convolutional and Recurrent Neural Networks for Classification of Focal Liver Lesions in Multi-phase CT Images

    Dong Liang;Lanfen Lin;Hongjie Hu;Qiaowei Zhang

  • Multi-Level and Multi-Scale Spatial and Spectral Fusion CNN for Hyperspectral Image Super-Resolution

    Xian-Hua Han;YinQiang Zheng;Yen-Wei Chen

  • Feature Selection Using Recursive Feature Elimination for Handwritten Digit Recognition

    Xiangyan Zeng;Yen-Wei Chen;Caixia Tao;Deborah van Alphen

  • Automatic gender recognition based on pixel-pattern-based texture feature

    Huchuan Lu;Yingjie Huang;Yenwei Chen;Yenwei Chen;Deli Yang

  • Abdominal multi-organ segmentation of CT images based on hierarchical spatial modeling of organ interrelations

    Toshiyuki Okada;Yasuhide Yoshida;Masatoshi Hori;Ronald M. Summers

  • A novel method for gaze tracking by local pattern model and support vector regressor

    Hu-Chuan Lu;Guo-Liang Fang;Chao Wang;Yen-Wei Chen

  • Computer-Assisted Preoperative Planning for Reduction of Proximal Femoral Fracture Using 3-D-CT Data

    T. Okada;Y. Iwasaki;T. Koyama;N. Sugano

  • 2009 Fifth International Conference on Natural Computation

    Motoi Kinishi;Toshiyuki Okada;Masatoshi Hori;Yen-Wei Chen

Frequent Co-Authors

Ruofeng Tong
Ruofeng Tong Zhejiang University
Yoshinobu Sato
Yoshinobu Sato Nara Institute of Science and Technology
Huchuan Lu
Huchuan Lu Dalian University of Technology
Hanqing Lu
Hanqing Lu Chinese Academy of Sciences
Jian Cheng
Jian Cheng Chinese Academy of Sciences
Yasushi Yagi
Yasushi Yagi Osaka University
Qingshan Liu
Qingshan Liu Nanjing University of Information Science and Technology
Yinqiang Zheng
Yinqiang Zheng National Institute of Informatics

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