World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
12641
World Ranking
6352
National Ranking
84

Jen Hong Tan 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 Jen Hong Tan 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: 79 publications — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Jen Hong Tan 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 Jen Hong Tan 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Jen Hong Tan is affiliated with the National University of Singapore in Singapore. Their research spans multiple areas at the intersection of medicine and computer science, with a focus on artificial intelligence applications in healthcare and neuroscience.

Their work addresses diverse topics including EEG and brain-computer interfaces, artificial intelligence in healthcare and education, machine learning in healthcare, ECG monitoring and analysis, colorectal cancer screening and detection, AI in cancer detection, and emotion and mood recognition.

Frequent coauthors of Jen Hong Tan include Gerald Gui Ren Sng, Joshua Yi Min Tung, U. Rajendra Acharya, Daniel Yan Zheng Lim, and Ru-San Tan.

Tan has published studies in several venues, notably:

  • Computer Methods and Programs in Biomedicine
  • arXiv (Cornell University)
  • Frontiers in Neuroscience
  • JMIR AI
  • Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery

Some recent publications include:

  • "An Investigation of Deep Learning Models for EEG-Based Emotion Recognition" (2020) published in Frontiers in Neuroscience
  • "Automated anxiety detection using probabilistic binary pattern with ECG signals" (2024) in Computer Methods and Programs in Biomedicine
  • "Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation" (2024) in Computer Methods and Programs in Biomedicine
  • "Machine Learning-Based Prediction for High Health Care Utilizers by Using a Multi-Institutional Diabetes Registry: Model Training and Evaluation" (2024) in JMIR AI
  • "Automated Detection of Neurological and Mental Health Disorders Using EEG Signals and Artificial Intelligence: A Systematic Review" (2025) in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery

Their research contributions encompass subfields such as artificial intelligence, cognitive neuroscience, cardiology and cardiovascular medicine, health informatics, and oncology. This diversified expertise aligns with their multidisciplinary approach to healthcare challenges.

Best Publications

  • Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

    U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Shu Lih Oh;Yuki Hagiwara;Jen Hong Tan

  • A deep convolutional neural network model to classify heartbeats

    U. Rajendra Acharya;Shu Lih Oh;Yuki Hagiwara;Jen Hong Tan

  • Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals

    U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Hamido Fujita;Shu Lih Oh;Yuki Hagiwara

  • Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network

    U. Rajendra Acharya;Hamido Fujita;Oh Shu Lih;Yuki Hagiwara

  • Automated EEG-based screening of depression using deep convolutional neural network.

    U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Shu Lih Oh;Yuki Hagiwara;Jen Hong Tan

  • Deep convolution neural network for accurate diagnosis of glaucoma using digital fundus images

    U Raghavendra;Hamido Fujita;Sulatha V Bhandary;Anjan Gudigar

  • Thermography Based Breast Cancer Detection Using Texture Features and Support Vector Machine

    U. Rajendra Acharya;E. Y. Ng;Jen-Hong Tan;S. Vinitha Sree

  • Automated detection of coronary artery disease using different durations of ECG segments with convolutional neural network

    U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Hamido Fujita;Oh Shu Lih;Muhammad Adam

  • Application of stacked convolutional and long short-term memory network for accurate identification of CAD ECG signals.

    Jen Hong Tan;Yuki Hagiwara;Winnie Pang;Ivy Lim

  • Deep convolutional neural network for the automated diagnosis of congestive heart failure using ECG signals

    U. Rajendra Acharya;Hamido Fujita;Shu Lih Oh;Yuki Hagiwara

  • Infrared thermography on ocular surface temperature: A review

    Jen-Hong Tan;E.Y.K. Ng;U. Rajendra Acharya;C. Chee

  • Automated identification of shockable and non-shockable life-threatening ventricular arrhythmias using convolutional neural network

    U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Hamido Fujita;Shu Lih Oh;U. Raghavendra

  • Automated segmentation of exudates, haemorrhages, microaneurysms using single convolutional neural network

    Jen Hong Tan;Hamido Fujita;Sobha Sivaprasad;Sulatha V. Bhandary

  • Automated detection and localization of myocardial infarction using electrocardiogram

    U. Rajendra Acharya;Hamido Fujita;Vidya K. Sudarshan;Shu Lih Oh

  • Application of empirical mode decomposition (emd) for automated detection of epilepsy using EEG signals.

    Roshan Joy Martis;U. Rajendra Acharya;U. Rajendra Acharya;Jen Hong Tan;Andrea Petznick

  • Segmentation of optic disc, fovea and retinal vasculature using a single convolutional neural network

    Jen Hong Tan;U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Sulatha V. Bhandary;Kuang Chua Chua

  • An Integrated Index for the Identification of Diabetic Retinopathy Stages Using Texture Parameters

    U. Rajendra Acharya;E. Y. Ng;Jen-Hong Tan;S. Vinitha Sree

  • Computer-aided diagnosis of atrial fibrillation based on ECG Signals: A review

    Yuki Hagiwara;Hamido Fujita;Shu Lih Oh;Jen Hong Tan

  • Computer-Aided diagnosis of glaucoma using fundus images: A review

    Yuki Hagiwara;Joel En Wei Koh;Jen Hong Tan;Sulatha V. Bhandary

  • An Investigation of Deep Learning Models for EEG-Based Emotion Recognition

    Unknown

  • Age-related Macular Degeneration detection using deep convolutional neural network

    Jen Hong Tan;Sulatha V. Bhandary;Sobha Sivaprasad;Yuki Hagiwara

Frequent Co-Authors

U. Rajendra Acharya
U. Rajendra Acharya University of Southern Queensland
Shu Lih Oh
Shu Lih Oh Ngee Ann Polytechnic
Hamido Fujita
Hamido Fujita University of Technology Malaysia
Eddie Y. K. Ng
Eddie Y. K. Ng Nanyang Technological University
Joel En Wei Koh
Joel En Wei Koh Ngee Ann Polytechnic
Markus R. Wenk
Markus R. Wenk Hamad bin Khalifa University
Vinod Chandran
Vinod Chandran Queensland University of Technology
Hojjat Adeli
Hojjat Adeli The Ohio State University
Guanghou Shui
Guanghou Shui Chinese Academy of Sciences
Jasjit S. Suri
Jasjit S. Suri University of Idaho

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