World's Best Scientists 2026 revealed!
Yuanyuan Wang

Yuanyuan Wang

D-Index & Metrics

Computer Science

D-Index
43
Citations
9363
World Ranking
7880
National Ranking
1035

Yuanyuan Wang 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 Yuanyuan Wang 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: 331 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Yuanyuan Wang 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 Yuanyuan Wang 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Yuanyuan Wang is affiliated with Fudan University in China and has contributed extensively to the field of medicine, with a particular focus on radiology, nuclear medicine, and medical imaging. Their research intersects with computer vision and pattern recognition, biomedical engineering, surgery, and pulmonary and respiratory medicine.

Their recent published papers include:

  • Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer (2020, Nature Communications)
  • A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging (2020, Medical Image Analysis)
  • Lymph node metastasis prediction of papillary thyroid carcinoma based on transfer learning radiomics (2020, Nature Communications)
  • Complement C1q-dependent excitatory and inhibitory synapse elimination by astrocytes and microglia in Alzheimer's disease mouse models (2022, Nature Aging)
  • Ultrasound-Based Radiomic Nomogram for Predicting Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma (2020, Academic Radiology)

Yuanyuan Wang frequently collaborates with several researchers, with notable coauthors including:

  • Yi Guo
  • Jinhua Yu
  • Jing Jiao
  • Shichong Zhou
  • Guoqing Wu

Their publications have appeared repeatedly in a variety of venues. The most frequent venues for their work are:

  • Research Square (Research Square)
  • arXiv (Cornell University)
  • Frontiers in Oncology
  • Biomedical Signal Processing and Control
  • Medical Image Analysis

The main fields of study in their body of work focus on medicine, with particular emphasis on the following subfields:

  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering
  • Surgery
  • Pulmonary and Respiratory Medicine

Yuanyuan Wang's research topics include:

  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Medical Image Segmentation Techniques
  • Photoacoustic and Ultrasonic Imaging
  • Advanced Neural Network Applications
  • Thyroid Cancer Diagnosis and Treatment
  • Cerebrovascular and Carotid Artery Diseases

Best Publications

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging.

    Zhaohan Xiong;Qing Xia;Zhiqiang Hu;Ning Huang

  • Deep Learning based Radiomics (DLR) and its usage in noninvasive IDH1 prediction for low grade glioma.

    Zeju Li;Yuanyuan Wang;Jinhua Yu;Yi Guo

  • Lymph node metastasis prediction of papillary thyroid carcinoma based on transfer learning radiomics

    Jinhua Yu;Yinhui Deng;Tongtong Liu;Jin Zhou

  • Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model

    Yuzhou Hu;Yi Guo;Yuanyuan Wang;Jinhua Yu

  • Robust sleep stage classification with single-channel EEG signals using multimodal decomposition and HMM-based refinement

    Dihong Jiang;Ya-nan Lu;Yu Ma;Yuanyuan Wang

  • Doppler ultrasound signal denoising based on wavelet frames

    Yu Zhang;Yuanyuan Wang;Weiqi Wang;Bin Liu

  • Ultrasound speckle reduction by a SUSAN-controlled anisotropic diffusion method

    Jinhua Yu;Jinglu Tan;Yuanyuan Wang

  • Prediction of Lymph Node Metastasis in Patients With Papillary Thyroid Carcinoma: A Radiomics Method Based on Preoperative Ultrasound Images:

    Tongtong Liu;Shichong Zhou;Jinhua Yu;Yi Guo

  • Speckle filtering of ultrasonic images using a modified non local-based algorithm

    Yanhui Guo;Yuanyuan Wang;T. Hou

  • Sonoelastomics for Breast Tumor Classification: A Radiomics Approach with Clustering-Based Feature Selection on Sonoelastography

    Qi Zhang;Yang Xiao;Jingfeng Suo;Jun Shi

  • Sparse Representation-Based Radiomics for the Diagnosis of Brain Tumors

    Guoqing Wu;Yinsheng Chen;Yuanyuan Wang;Jinhua Yu

  • A rough margin based support vector machine

    Junhua Zhang;Yuanyuan Wang

  • Segmentation of Fetal Left Ventricle in Echocardiographic Sequences Based on Dynamic Convolutional Neural Networks

    Li Yu;Yi Guo;Yuanyuan Wang;Jinhua Yu

  • Noise reduction and edge detection via kernel anisotropic diffusion

    Jinhua Yu;Yuanyuan Wang;Yuzhong Shen

  • An Ultrasound Radiomics Nomogram for Preoperative Prediction of Central Neck Lymph Node Metastasis in Papillary Thyroid Carcinoma.

    Shi-Chong Zhou;Tong-Tong Liu;Jin Zhou;Yun-Xia Huang

  • Automatic Cobb Measurement of Scoliosis Based on Fuzzy Hough Transform with Vertebral Shape Prior

    Junhua Zhang;Edmond Lou;Lawrence H. Le;Douglas L. Hill

  • Robust phase-based texture descriptor for classification of breast ultrasound images.

    Lingyun Cai;Xin Wang;Yuanyuan Wang;Yi Guo

  • Comparison of the application of B-mode and strain elastography ultrasound in the estimation of lymph node metastasis of papillary thyroid carcinoma based on a radiomics approach

    Tongtong Liu;Xifeng Ge;Jinhua Yu;Yi Guo

  • Predicting termination of atrial fibrillation based on the structure and quantification of the recurrence plot

    Rongrong Sun;Yuanyuan Wang

  • Total variation based gradient descent algorithm for sparse-view photoacoustic image reconstruction.

    Yan Zhang;Yuanyuan Wang;Chen Zhang

  • A computer-aided Cobb angle measurement method and its reliability.

    Junhua Zhang;Edmond Lou;Xinling Shi;Yuanyuan Wang

Frequent Co-Authors

Rob J. van der Geest
Rob J. van der Geest Leiden University Medical Center
Yong-Ping Zheng
Yong-Ping Zheng Hong Kong Polytechnic University
Zhongping Chen
Zhongping Chen University of California, Irvine
Daniel Rueckert
Daniel Rueckert Technical University of Munich
Yefeng Zheng
Yefeng Zheng Tencent (China)
Wenjia Bai
Wenjia Bai Imperial College London
Hairong Zheng
Hairong Zheng Chinese Academy of Sciences
Daru Lu
Daru Lu Fudan University
Andreas Maier
Andreas Maier University of Erlangen-Nuremberg
Tom Vercauteren
Tom Vercauteren King's College London

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