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Computer Science
Australia
2026

D-Index & Metrics

Computer Science

D-Index
139
Citations
77251
World Ranking
71
National Ranking
2

Research.com Recognitions

  • 2026 - Research.com Computer Science in Australia Leader Award
  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

U. Rajendra Acharya is affiliated with the University of Southern Queensland in Australia. Their research spans multiple fields including Medicine, Computer Science, and Neuroscience, with a notable focus on interdisciplinary applications of technology in healthcare.

The main areas of study for Acharya include Medicine with 573 publications, Computer Science with 287 publications, and Neuroscience with 275 publications. Within these fields, the subfields of Cognitive Neuroscience, Artificial Intelligence, Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging, and Biomedical Engineering represent significant domains of their work.

The scientist's research topics cover a range of applications, particularly in biomedical signal processing and artificial intelligence. Their principal topics include:

  • EEG and Brain-Computer Interfaces
  • ECG Monitoring and Analysis
  • AI in cancer detection
  • COVID-19 diagnosis using AI
  • Radiomics and Machine Learning in Medical Imaging
  • Functional Brain Connectivity Studies
  • Non-Invasive Vital Sign Monitoring

Acharya has published extensively in prominent venues, with frequent contributions to:

  • Computers in Biology and Medicine (57 publications)
  • arXiv (Cornell University) (33 publications)
  • IEEE Access (32 publications)
  • Computer Methods and Programs in Biomedicine (31 publications)
  • International Journal of Environmental Research and Public Health (17 publications)

Their recent papers illustrate a strong emphasis on the application of deep learning and artificial intelligence in medical diagnostics and imaging:

  • "Automated detection of COVID-19 cases using deep neural networks with X-ray images" (2020), Computers in Biology and Medicine
  • "A review of uncertainty quantification in deep learning: Techniques, applications and challenges" (2021), Information Fusion
  • "Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks" (2020), Computers in Biology and Medicine
  • "ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis" (2020), Future Generation Computer Systems
  • "Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011-2022)" (2022), Computer Methods and Programs in Biomedicine

The scientist frequently collaborates with several researchers, including:

  • Prabal Datta Barua
  • Ru-San Tan
  • Şengül Doğan
  • Türker Tuncer
  • Mehmet Bayğın

In addition to journal articles, Acharya has contributed to book publications, notably with Springer Science+Business Media, including the titled work "Proceedings of International Conference on Communication, Circuits, and Systems" published in 2021.

Best Publications

  • Heart rate variability: a review

    U. Rajendra Acharya;K. Paul Joseph;N. Kannathal;Choo Min Lim

  • Automated detection of COVID-19 cases using deep neural networks with X-ray images.

    Tulin Ozturk;Muhammed Talo;Eylul Azra Yildirim;Ulas Baran Baloglu

  • A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

    Moloud Abdar;Farhad Pourpanah;Sadiq Hussain;Dana Rezazadegan

  • 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

  • Deep learning for healthcare applications based on physiological signals: A review.

    Oliver Faust;Yuki Hagiwara;Tan Jen Hong;Oh Shu Lih

  • Entropies for detection of epilepsy in EEG

    N. Kannathal;Min Lim Choo;U. Rajendra Acharya;P. K. Sadasivan

  • 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 EEG analysis of epilepsy: A review

    U. Rajendra Acharya;S. Vinitha Sree;G. Swapna;Roshan Joy Martis

  • Arrhythmia detection using deep convolutional neural network with long duration ECG signals.

    Özal Yildirim;Pawel Plawiak;Ru San Tan;U. Rajendra Acharya

  • Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks.

    Ali Abbasian Ardakani;Alireza Rajabzadeh Kanafi;U. Rajendra Acharya;Nazanin Khadem

  • ECG beat classification using PCA, LDA, ICA and Discrete Wavelet Transform

    Roshan Joy Martis;U. Rajendra Acharya;U. Rajendra Acharya;Lim Choo Min

  • 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 diagnosis of epileptic EEG using entropies

    U. Rajendra Acharya;Filippo Molinari;S. Vinitha Sree;Subhagata Chattopadhyay

  • 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

  • ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis

    Mohammad Ehsan Basiri;Shahla Nemati;Moloud Abdar;Erik Cambria

  • 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

  • Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis.

    Oliver Faust;U. Rajendra Acharya;Hojjat Adeli;Amir Adeli

  • Non-linear analysis of EEG signals at various sleep stages

    U Rajendra Acharya;Oliver Faust;N. Kannathal;TjiLeng Chua

  • Computer-aided diagnosis of diabetic retinopathy: A review

    Muthu Rama Krishnan Mookiah;U. Rajendra Acharya;U. Rajendra Acharya;Chua Kuang Chua;Choo Min Lim

Frequent Co-Authors

Jasjit S. Suri
Jasjit S. Suri University of Idaho
Jen Hong Tan
Jen Hong Tan Singapore General Hospital
Filippo Molinari
Filippo Molinari Polytechnic University of Turin
Oliver Faust
Oliver Faust Sheffield Hallam University
S. Vinitha Sree
S. Vinitha Sree Nanyang Technological University
Hamido Fujita
Hamido Fujita University of Technology Malaysia
Shu Lih Oh
Shu Lih Oh Ngee Ann Polytechnic
Joel En Wei Koh
Joel En Wei Koh Ngee Ann Polytechnic
Eddie Y. K. Ng
Eddie Y. K. Ng Nanyang Technological University
Ram Bilas Pachori
Ram Bilas Pachori Indian Institute of Technology Indore

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