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2025

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Rising Stars

D-Index
36
Citations
9539
World Ranking
784
National Ranking
15

Computer Science

D-Index
40
Citations
11028
World Ranking
9083
National Ranking
115

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Shu Lih Oh is affiliated with Ngee Ann Polytechnic in Singapore. Their research intersects medicine and neuroscience, with a strong focus on applied and clinical aspects reflected across numerous publications.

The primary fields of study for this scientist are:

  • Medicine
  • Neuroscience

Notable subfields include:

  • Cognitive Neuroscience
  • Cardiology and Cardiovascular Medicine
  • Psychiatry and Mental health
  • Pulmonary and Respiratory Medicine
  • Biomedical Engineering

The main topics in their body of work cover:

  • ECG Monitoring and Analysis
  • EEG and Brain-Computer Interfaces
  • Phonocardiography and Auscultation Techniques
  • Autism Spectrum Disorder Research
  • Attention Deficit Hyperactivity Disorder
  • Neuroscience and Neural Engineering
  • Non-Invasive Vital Sign Monitoring

Frequent coauthors collaborating with Shu Lih Oh include:

  • U. Rajendra Acharya
  • Jahmunah Vicnesh
  • Edward J. Ciaccio
  • Prabal Datta Barua
  • Ru-San Tan

Common publication venues reflect the scientist's focus on biomedical and computational research:

  • Computer Methods and Programs in Biomedicine
  • Computers in Biology and Medicine
  • International Journal of Environmental Research and Public Health
  • Neural Computing and Applications
  • Applied Sciences

Recent significant papers include:

  • Artificial Intelligence Enabled Personalised Assistive Tools to Enhance Education of Children with Neurodevelopmental Disorders-A Review, 2022, International Journal of Environmental Research and Public Health
  • Classification of heart sound signals using a novel deep WaveNet model, 2020, Computer Methods and Programs in Biomedicine
  • Explainable detection of myocardial infarction using deep learning models with Grad-CAM technique on ECG signals, 2022, Computers in Biology and Medicine
  • Automated detection of conduct disorder and attention deficit hyperactivity disorder using decomposition and nonlinear techniques with EEG signals, 2021, Computer Methods and Programs in Biomedicine
  • Automated Detection of Sleep Stages Using Deep Learning Techniques: A Systematic Review of the Last Decade (2010-2020), 2020, Applied Sciences

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 diagnosis of arrhythmia using combination of CNN and LSTM techniques with variable length heart beats

    Shu Lih Oh;Eddie Yin Kwee Ng;Ru San Tan;U. Rajendra Acharya

  • 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

  • A deep learning approach for Parkinson’s disease diagnosis from EEG signals

    Shu Lih Oh;Yuki Hagiwara;U. Raghavendra;Rajamanickam Yuvaraj

  • 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

  • Deep Convolutional Neural Network Model for Automated Diagnosis of Schizophrenia Using EEG Signals

    Shu Lih Oh;Jahmunah Vicnesh;Edward J Ciaccio;Rajamanickam Yuvaraj

  • 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 detection and localization of myocardial infarction using electrocardiogram

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

  • Characterization of focal EEG signals: A review

    U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Yuki Hagiwara;Sunny Nitin Deshpande;S. Suren

  • Automated detection of schizophrenia using nonlinear signal processing methods.

    V. Jahmunah;Shu Lih Oh;V. Rajinikanth;Edward J. Ciaccio

  • Comprehensive electrocardiographic diagnosis based on deep learning.

    Oh Shu Lih;V Jahmunah;Tan Ru San;Edward J Ciaccio

  • Automated beat-wise arrhythmia diagnosis using modified U-net on extended electrocardiographic recordings with heterogeneous arrhythmia types.

    Shu Lih Oh;Eddie Yin Kwee Ng;Ru San Tan;U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya

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

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

  • Classification of heart sound signals using a novel deep WaveNet model.

    Shu Lih Oh;V. Jahmunah;Chui Ping Ooi;Ru-San Tan

  • Application of higher-order spectra for the characterization of Coronary artery disease using electrocardiogram signals

    U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Vidya K. Sudarshan;Joel E.W. Koh;Roshan Joy Martis

  • Automated detection of conduct disorder and attention deficit hyperactivity disorder using decomposition and nonlinear techniques with EEG signals.

    Hui Tian Tor;Chui Ping Ooi;Nikki Sj Lim-Ashworth;Joel Koh En Wei

  • Automated Detection of Sleep Stages Using Deep Learning Techniques: A Systematic Review of the Last Decade (2010–2020)

    Hui Wen Loh;Chui Ping Ooi;Jahmunah Vicnesh;Shu Lih Oh

  • Computer-aided diagnosis of congestive heart failure using ECG signals - A review.

    V. Jahmunah;Shu Lih Oh;Joel Koh En Wei;Edward J Ciaccio

  • Automated characterization of coronary artery disease, myocardial infarction, and congestive heart failure using contourlet and shearlet transforms of electrocardiogram signal

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

Frequent Co-Authors

U. Rajendra Acharya
U. Rajendra Acharya University of Southern Queensland
Jen Hong Tan
Jen Hong Tan Singapore General Hospital
Joel En Wei Koh
Joel En Wei Koh Ngee Ann Polytechnic
Eddie Y. K. Ng
Eddie Y. K. Ng Nanyang Technological University
Hamido Fujita
Hamido Fujita University of Technology Malaysia
N. Arunkumar
N. Arunkumar SASTRA University
Oliver Faust
Oliver Faust Sheffield Hallam University
Filippo Molinari
Filippo Molinari Polytechnic University of Turin
Hojjat Adeli
Hojjat Adeli The Ohio State University
Daniel S. S. Fung
Daniel S. S. Fung Institute of Mental Health

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