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Computer Science
UK
2025

D-Index & Metrics

Computer Science

D-Index
88
Citations
24667
World Ranking
694
National Ranking
103

Shuihua 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 Shuihua 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: 372 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Shuihua 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 Shuihua 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: 88 D-Index — 95th percentile

95% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in United Kingdom Leader Award
  • 2023 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Computer Science in United Kingdom Leader Award

Overview

Shuihua Wang is affiliated with Xi'an Jiaotong-Liverpool University in China and has contributed extensively to research in computer science and medicine. Their body of work encompasses a wide range of topics including artificial intelligence applications in medical imaging and diagnosis.

Their recent publications include:

  • A review on extreme learning machine, 2021, Multimedia Tools and Applications
  • Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation, 2020, Information Fusion
  • Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network, 2020, Information Fusion
  • Improved Breast Cancer Classification Through Combining Graph Convolutional Network and Convolutional Neural Network, 2020, Information Processing & Management
  • Deep learning in food category recognition, 2023, Information Fusion

Frequent coauthors working alongside Shuihua Wang include:

  • Yudong Zhang
  • J. M. Górriz
  • Junding Sun
  • Siyuan Lu
  • Chaosheng Tang

Shuihua Wang's research has been published frequently in the following venues:

  • arXiv (Cornell University)
  • Computers, materials & continua/Computers, materials & continua (Print)
  • Information Fusion
  • Neurocomputing
  • CAAI Transactions on Intelligence Technology

The scientist has also contributed to book publications through the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, with titles such as Multimedia Technology and Enhanced Learning released in 2020 and 2021.

Their main fields of study focus on:

  • Computer Science
  • Medicine

Within these broad areas, Shuihua Wang's subfields of study include:

  • Radiology, Nuclear Medicine and Imaging
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Neurology
  • Biomedical Engineering

The primary topics covered across their research encompass:

  • COVID-19 diagnosis using AI
  • AI in cancer detection
  • Brain Tumor Detection and Classification
  • Radiomics and Machine Learning in Medical Imaging
  • Advanced Neural Network Applications
  • Anomaly Detection Techniques and Applications
  • Digital Imaging for Blood Diseases

Best Publications

  • A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

    Yudong Zhang;Shuihua Wang;Shuihua Wang;Genlin Ji

  • Binary PSO with mutation operator for feature selection using decision tree applied to spam detection

    Yudong Zhang;Shuihua Wang;Preetha Phillips;Genlin Ji

  • A review on extreme learning machine

    Jian Wang;Siyuan Lu;Shui-Hua Wang;Yu-Dong Zhang;Yu-Dong Zhang

  • A hybrid method for MRI brain image classification

    Yudong Zhang;Zhengchao Dong;Lenan Wu;Shuihua Wang

  • Advances in Multimodal Data Fusion in Neuroimaging: Overview, Challenges, and Novel Orientation

    Yu-Dong Zhang;Yu-Dong Zhang;Zhengchao Dong;Shui-Hua Wang;Shui-Hua Wang;Shui-Hua Wang;Xiang Yu

  • Image based fruit category classification by 13-layer deep convolutional neural network and data augmentation

    Yu-Dong Zhang;Zhengchao Dong;Xianqing Chen;Wenjuan Jia

  • Classification of Alzheimer’s Disease Based on Eight-Layer Convolutional Neural Network with Leaky Rectified Linear Unit and Max Pooling

    Shui-Hua Wang;Preetha Phillips;Yuxiu Sui;Bin Liu

  • Fruit classification using computer vision and feedforward neural network

    Yudong Zhang;Shuihua Wang;Genlin Ji;Preetha Phillips

  • Detection of subjects and brain regions related to Alzheimer's disease using 3D MRI scans based on eigenbrain and machine learning.

    Yudong Zhang;Zhengchao Dong;Preetha Phillips;Shuihua Wang;Shuihua Wang

  • Improved Breast Cancer Classification Through Combining Graph Convolutional Network and Convolutional Neural Network

    Yu-Dong Zhang;Yu-Dong Zhang;Suresh Chandra Satapathy;David S. Guttery;Juan Manuel Górriz

  • Covid-19 Classification by FGCNet with Deep Feature Fusion from Graph Convolutional Network and Convolutional Neural Network.

    Shui Hua Wang;Shui Hua Wang;Shui Hua Wang;Vishnu Varthanan Govindaraj;Juan Manuel Górriz;Juan Manuel Górriz;Xin Zhang

  • Facial Emotion Recognition Based on Biorthogonal Wavelet Entropy, Fuzzy Support Vector Machine, and Stratified Cross Validation

    Yu-Dong Zhang;Zhang-Jing Yang;Hui-Min Lu;Xing-Xing Zhou

  • MAGNETIC RESONANCE BRAIN IMAGE CLASSIFICATION BY AN IMPROVED ARTIFICIAL BEE COLONY ALGORITHM

    Yudong Zhang;Lenan Wu;Shuihua Wang

  • Preclinical Diagnosis of Magnetic Resonance (MR) Brain Images via Discrete Wavelet Packet Transform with Tsallis Entropy and Generalized Eigenvalue Proximal Support Vector Machine (GEPSVM)

    Yudong Zhang;Zhengchao Dong;Shuihua Wang;Genlin Ji

  • A Review of Deep Learning on Medical Image Analysis

    Jian Wang;Hengde Zhu;Shui-Hua Wang;Shui-Hua Wang;Yu-Dong Zhang;Yu-Dong Zhang

  • Classification of Alzheimer Disease Based on Structural Magnetic Resonance Imaging by Kernel Support Vector Machine Decision Tree

    Yudong Zhang;Shuihua Wang;Zhengchao Dong

  • A review of IoT applications in healthcare

    Unknown

  • DenseNet-201-Based Deep Neural Network with Composite Learning Factor and Precomputation for Multiple Sclerosis Classification

    Shui-Hua Wang;Yu-Dong Zhang

  • Comparison of machine learning methods for stationary wavelet entropy-based multiple sclerosis detection

    Yudong Zhang;Siyuan Lu;Xingxing Zhou;Ming Yang

  • COVID-19 classification by CCSHNet with deep fusion using transfer learning and discriminant correlation analysis

    Shui-Hua Wang;Shui-Hua Wang;Shui-Hua Wang;Deepak Ranjan Nayak;David S. Guttery;Xin Zhang

  • Intelligent facial emotion recognition based on stationary wavelet entropy and Jaya algorithm

    Shui-Hua Wang;Preetha Phillips;Zheng-Chao Dong;Yu-Dong Zhang

  • Detection of abnormal brain in MRI via improved AlexNet and ELM optimized by chaotic bat algorithm

    Siyuan Lu;Shui-Hua Wang;Shui-Hua Wang;Yu-Dong Zhang;Yu-Dong Zhang;Yu-Dong Zhang

  • Feed-forward neural network optimized by hybridization of PSO and ABC for abnormal brain detection

    Shuihua Wang;Yudong Zhang;Zhengchao Dong;Sidan Du

  • Automated classification of brain images using wavelet-energy and biogeography-based optimization

    Gelan Yang;Yudong Zhang;Jiquan Yang;Genlin Ji

Frequent Co-Authors

Yudong Zhang
Yudong Zhang University of Leicester
Lenan Wu
Lenan Wu Southeast University
Yin Zhang
Yin Zhang University of Electronic Science and Technology of China
Ti-Fei Yuan
Ti-Fei Yuan Shanghai Jiao Tong University
Huimin Lu
Huimin Lu Kyushu Institute of Technology
Khan Muhammad
Khan Muhammad Sungkyunkwan University
Juan Manuel Górriz
Juan Manuel Górriz University of Granada
Yuankai Huo
Yuankai Huo Vanderbilt University
Javier Ramírez
Javier Ramírez University of Granada
Yingli Tian
Yingli Tian City University of New York

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