U. Rajendra Acharya

87.8k total citations · 44 hit papers
966 papers, 63.3k citations indexed

About

U. Rajendra Acharya is a scholar working on Cognitive Neuroscience, Cardiology and Cardiovascular Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, U. Rajendra Acharya has authored 966 papers receiving a total of 63.3k indexed citations (citations by other indexed papers that have themselves been cited), including 296 papers in Cognitive Neuroscience, 290 papers in Cardiology and Cardiovascular Medicine and 258 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in U. Rajendra Acharya's work include EEG and Brain-Computer Interfaces (279 papers), ECG Monitoring and Analysis (201 papers) and Heart Rate Variability and Autonomic Control (93 papers). U. Rajendra Acharya is often cited by papers focused on EEG and Brain-Computer Interfaces (279 papers), ECG Monitoring and Analysis (201 papers) and Heart Rate Variability and Autonomic Control (93 papers). U. Rajendra Acharya collaborates with scholars based in Singapore, Australia and India. U. Rajendra Acharya's co-authors include Jen Hong Tan, Ru‐San Tan, Yuki Hagiwara, Shu Lih Oh, Jasjit S. Suri, Özal Yıldırım, E. Y. K. Ng, Oliver Faust, N. Kannathal and Choo Min Lim and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

U. Rajendra Acharya

939 papers receiving 61.1k citations

Hit Papers

Heart rate variability: a review 2005 2026 2012 2019 2006 2020 2021 2017 2017 500 1000 1.5k 2.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Heart rate variability: a review
    2006 2.0k citations U. Rajendra Acharya et al. profile →
  2. Automated detection of COVID-19 cases using deep neural networks with X-ray images
    2020 1.7k citations U. Rajendra Acharya et al. Computers in Biology and Medicine profile →
  3. A review of uncertainty quantification in deep learning: Techniques, applications and challenges
    2021 1.5k citations Moloud Abdar, Abbas Khosravi et al. Information Fusion profile →
  4. Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals
    2017 1.2k citations U. Rajendra Acharya, Shu Lih Oh et al. Computers in Biology and Medicine profile →
  5. A deep convolutional neural network model to classify heartbeats
    2017 987 citations U. Rajendra Acharya, Shu Lih Oh et al. Computers in Biology and Medicine profile →
  6. Deep learning for healthcare applications based on physiological signals: A review
    2018 680 citations Oliver Faust, Yuki Hagiwara et al. Computer Methods and Programs in Biomedicine profile →
  7. Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals
    2017 678 citations U. Rajendra Acharya, Shu Lih Oh et al. profile →
  8. Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks
    2020 607 citations U. Rajendra Acharya et al. Computers in Biology and Medicine profile →
  9. Arrhythmia detection using deep convolutional neural network with long duration ECG signals
    2018 604 citations Ru‐San Tan, U. Rajendra Acharya et al. Computers in Biology and Medicine profile →
  10. Entropies for detection of epilepsy in EEG
    2005 597 citations U. Rajendra Acharya et al. Computer Methods and Programs in Biomedicine profile →
  11. Automated EEG analysis of epilepsy: A review
    2013 593 citations U. Rajendra Acharya et al. Knowledge-Based Systems profile →
  12. Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network
    2017 557 citations U. Rajendra Acharya, Oh Shu Lih et al. profile →
  13. ECG beat classification using PCA, LDA, ICA and Discrete Wavelet Transform
    2013 553 citations U. Rajendra Acharya et al. Biomedical Signal Processing and Control profile →
  14. Automated diagnosis of arrhythmia using combination of CNN and LSTM techniques with variable length heart beats
    2018 535 citations Shu Lih Oh, E. Y. K. Ng et al. Computers in Biology and Medicine profile →
  15. ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis
    2020 519 citations Moloud Abdar, U. Rajendra Acharya et al. profile →
  16. Automated diagnosis of epileptic EEG using entropies
    2011 468 citations U. Rajendra Acharya, Filippo Molinari et al. Biomedical Signal Processing and Control profile →
  17. Automated EEG-based screening of depression using deep convolutional neural network
    2018 450 citations U. Rajendra Acharya, Shu Lih Oh et al. Computer Methods and Programs in Biomedicine profile →
  18. Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022)
    2022 438 citations Chui Ping Ooi, Silvia Seoni et al. Computer Methods and Programs in Biomedicine profile →
  19. A deep learning approach for Parkinson’s disease diagnosis from EEG signals
    2018 423 citations Shu Lih Oh, Yuki Hagiwara et al. profile →
  20. Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis
    2015 421 citations Oliver Faust, U. Rajendra Acharya et al. profile →
  21. Application of entropies for automated diagnosis of epilepsy using EEG signals: A review
    2015 391 citations U. Rajendra Acharya, Vidya K. Sudarshan et al. Knowledge-Based Systems profile →
  22. Application of deep transfer learning for automated brain abnormality classification using MR images
    2018 376 citations U. Rajendra Acharya et al. profile →
  23. Deep convolution neural network for accurate diagnosis of glaucoma using digital fundus images
    2018 336 citations U. Raghavendra, Anjan Gudigar et al. profile →
  24. Classification of myocardial infarction with multi-lead ECG signals and deep CNN
    2019 335 citations Ru‐San Tan, U. Rajendra Acharya et al. profile →
  25. Computer-aided diagnosis of diabetic retinopathy: A review
    2013 335 citations U. Rajendra Acharya, E. Y. K. Ng et al. Computers in Biology and Medicine profile →
  26. SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach
    2019 334 citations U. Rajendra Acharya et al. profile →
  27. Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals
    2019 289 citations U. Rajendra Acharya, Filippo Molinari et al. Computers in Biology and Medicine profile →
  28. Application of stacked convolutional and long short-term memory network for accurate identification of CAD ECG signals
    2018 289 citations Jen Hong Tan, Yuki Hagiwara et al. Computers in Biology and Medicine profile →
  29. A new approach for arrhythmia classification using deep coded features and LSTM networks
    2019 279 citations Ru‐San Tan, Edward J. Ciaccio et al. Computer Methods and Programs in Biomedicine profile →
  30. Epileptic Seizures Detection Using Deep Learning Techniques: A Review
    2021 263 citations Roohallah Alizadehsani, Abbas Khosravi et al. profile →
  31. A new machine learning technique for an accurate diagnosis of coronary artery disease
    2019 248 citations Moloud Abdar, U. Rajendra Acharya et al. Computer Methods and Programs in Biomedicine profile →
  32. The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis
    2020 242 citations Massimo Salvi, U. Rajendra Acharya et al. Computers in Biology and Medicine profile →
  33. Application of artificial intelligence in wearable devices: Opportunities and challenges
    2021 223 citations Roohallah Alizadehsani, Abbas Khosravi et al. Computer Methods and Programs in Biomedicine profile →
  34. Transfer learning techniques for medical image analysis: A review
    2021 218 citations Chui Ping Ooi, Oliver Faust et al. Journal of Applied Biomedicine profile →
  35. Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review
    2020 215 citations U. Rajendra Acharya et al. Computers in Biology and Medicine profile →
  36. Remote patient monitoring using artificial intelligence: Current state, applications, and challenges
    2023 212 citations Raj Gururajan, U. Rajendra Acharya et al. profile →
  37. Deep Learning for Neuroimaging-based Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review
    2020 188 citations Roohallah Alizadehsani, Abbas Khosravi et al. profile →
  38. Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations
    2023 162 citations U. Rajendra Acharya et al. Information Fusion profile →
  39. Explainable detection of myocardial infarction using deep learning models with Grad-CAM technique on ECG signals
    2022 126 citations E. Y. K. Ng, Ru‐San Tan et al. Computers in Biology and Medicine profile →
  40. Emotion recognition in EEG signals using deep learning methods: A review
    2023 107 citations U. Rajendra Acharya et al. Computers in Biology and Medicine profile →
  41. Application of uncertainty quantification to artificial intelligence in healthcare: A review of last decade (2013–2023)
    2023 97 citations Silvia Seoni, Jahmunah Vicnesh et al. Computers in Biology and Medicine profile →
  42. Designing interpretable ML system to enhance trust in healthcare: A systematic review to proposed responsible clinician-AI-collaboration framework
    2024 77 citations Roohallah Alizadehsani, U. Rajendra Acharya et al. Information Fusion profile →
  43. Application of data fusion for automated detection of children with developmental and mental disorders: A systematic review of the last decade
    2023 76 citations Sonja March, Prabal Datta Barua et al. Information Fusion profile →
  44. An explainable and interpretable model for attention deficit hyperactivity disorder in children using EEG signals
    2023 68 citations U. Rajendra Acharya et al. Computers in Biology and Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
U. Rajendra Acharya Singapore 125 23.4k 19.6k 14.6k 11.6k 9.6k 966 63.3k
Stephen M. Smith United Kingdom 131 83.3k 3.6× 4.2k 0.2× 60.5k 4.1× 2.8k 0.2× 3.0k 0.3× 442 142.7k
Paul M. Thompson United States 157 34.1k 1.5× 15.4k 0.8× 25.6k 1.8× 2.7k 0.2× 2.4k 0.3× 2.1k 119.5k
Daniel Rueckert United Kingdom 88 6.6k 0.3× 2.3k 0.1× 20.2k 1.4× 5.5k 0.5× 5.1k 0.5× 591 44.6k
Jürgen Schmidhuber Switzerland 56 5.3k 0.2× 1.6k 0.1× 3.4k 0.2× 43.5k 3.8× 5.3k 0.6× 240 104.9k
Dinggang Shen United States 114 13.0k 0.6× 608 0.0× 20.7k 1.4× 12.1k 1.0× 5.5k 0.6× 1.3k 53.1k
Max A. Viergever Netherlands 85 2.3k 0.1× 1.6k 0.1× 17.9k 1.2× 3.6k 0.3× 6.4k 0.7× 563 35.8k
Alex Krizhevsky Canada 7 3.2k 0.1× 891 0.0× 6.1k 0.4× 24.9k 2.2× 4.7k 0.5× 7 70.5k
Jasjit S. Suri United States 61 2.0k 0.1× 6.2k 0.3× 4.8k 0.3× 2.2k 0.2× 2.1k 0.2× 436 15.2k
Jeffrey M. Hausdorff Israel 102 9.8k 0.4× 8.6k 0.4× 1.5k 0.1× 1.9k 0.2× 11.5k 1.2× 365 49.0k

Countries citing papers authored by U. Rajendra Acharya

Since Specialization
Citations

This map shows the geographic impact of U. Rajendra Acharya's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by U. Rajendra Acharya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites U. Rajendra Acharya more than expected).

Fields of papers citing papers by U. Rajendra Acharya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by U. Rajendra Acharya. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by U. Rajendra Acharya. The network helps show where U. Rajendra Acharya may publish in the future.

Co-authorship network of co-authors of U. Rajendra Acharya

This figure shows the co-authorship network connecting the top 25 collaborators of U. Rajendra Acharya. A scholar is included among the top collaborators of U. Rajendra Acharya based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with U. Rajendra Acharya. U. Rajendra Acharya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yang, Jing, et al.. (2025). A dual-method approach using autoencoders and transductive learning for remaining useful life estimation. Engineering Applications of Artificial Intelligence. 147. 110285–110285.
2.
Salvi, Massimo, Silvia Seoni, Andrea Campagner, et al.. (2025). Explainability and uncertainty: Two sides of the same coin for enhancing the interpretability of deep learning models in healthcare. International Journal of Medical Informatics. 197. 105846–105846. 14 indexed citations
3.
Atıla, Orhan, et al.. (2025). A novel uncertainty-aware liquid neural network for noise-resilient time series forecasting and classification. Chaos Solitons & Fractals. 193. 116130–116130. 3 indexed citations
4.
5.
Joseph, Lionel, Sujan Ghimire, Ravinesh C. Deo, et al.. (2024). Explainable hybrid deep learning framework for enhancing multi-step solar ultraviolet-B radiation predictions. Atmospheric Environment. 343. 120951–120951. 2 indexed citations
6.
Tuncer, Türker, et al.. (2024). N-BodyPat: Investigation on the dementia and Alzheimer's disorder detection using EEG signals. Knowledge-Based Systems. 304. 112510–112510. 1 indexed citations
7.
Tuncer, Türker, Şengül Doğan, Mehmet Bayğın, et al.. (2024). FLP: Factor lattice pattern-based automated detection of Parkinson's disease and specific language impairment using recorded speech. Computers in Biology and Medicine. 173. 108280–108280. 2 indexed citations
8.
Tuncer, Türker, et al.. (2024). A lightweight deep convolutional neural network model for skin cancer image classification. Applied Soft Computing. 162. 111794–111794. 15 indexed citations
9.
Sharifrazi, Danial, et al.. (2024). Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis: A machine learning approach. Biomedical Signal Processing and Control. 96. 106594–106594. 3 indexed citations
10.
Güler, Hasan, et al.. (2023). Application of novel DIRF feature selection algorithm for automated brain disease detection. Biomedical Signal Processing and Control. 85. 105006–105006. 6 indexed citations
11.
Abdar, Moloud, Farzad Masoudkabir, Leonardo Rundo, et al.. (2023). Binarized multi-gate mixture of Bayesian experts for cardiac syndrome X diagnosis: A clinician-in-the-loop scenario with a belief-uncertainty fusion paradigm. Information Fusion. 97. 101813–101813. 9 indexed citations
12.
Kabir, H M Dipu, Subrota Kumar Mondal, Abbas Khosravi, et al.. (2023). Uncertainty aware neural network from similarity and sensitivity. Applied Soft Computing. 149. 111027–111027. 5 indexed citations
13.
14.
Xu, Shuting, Ravinesh C. Deo, Jeffrey Soar, et al.. (2023). Automated detection of airflow obstructive diseases: A systematic review of the last decade (2013-2022). Computer Methods and Programs in Biomedicine. 241. 107746–107746. 5 indexed citations
15.
Kumar, Santhosh, U. Raghavendra, Anjan Gudigar, et al.. (2022). Development of a Computational Tool for the Estimation of Alveolar Bone Loss in Oral Radiographic Images. Computation. 10(1). 8–8. 2 indexed citations
16.
Sharma, Manish, et al.. (2022). Automated sleep apnea detection in pregnant women using wavelet-based features. Informatics in Medicine Unlocked. 32. 101026–101026. 8 indexed citations
17.
Koh, Joel E.W., Simona De Michele, Vidya K. Sudarshan, et al.. (2021). Automated interpretation of biopsy images for the detection of celiac disease using a machine learning approach. Computer Methods and Programs in Biomedicine. 203. 106010–106010. 18 indexed citations
18.
Patidar, Shivnarayan, et al.. (2020). Automated detection of abnormal heart sound signals using Fano-factor constrained tunable quality wavelet transform. Journal of Applied Biomedicine. 41(1). 111–126. 23 indexed citations
19.
Sharma, Manish, Ru‐San Tan, & U. Rajendra Acharya. (2019). Automated heartbeat classification and detection of arrhythmia using optimal orthogonal wavelet filters. Informatics in Medicine Unlocked. 16. 100221–100221. 65 indexed citations
20.
Faust, Oliver, Yuki Hagiwara, Jen Hong Tan, Oh Shu Lih, & U. Rajendra Acharya. (2018). Deep learning for healthcare applications based on physiological signals: A review. Computer Methods and Programs in Biomedicine. 161. 1–13. 680 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Stephen M. Smith Breakdown of academic impact, for papers by Paul M. Thompson Breakdown of academic impact, for papers by Daniel Rueckert Breakdown of academic impact, for papers by Jürgen Schmidhuber Breakdown of academic impact, for papers by Dinggang Shen Breakdown of academic impact, for papers by Max A. Viergever Breakdown of academic impact, for papers by Alex Krizhevsky Breakdown of academic impact, for papers by Jasjit S. Suri Breakdown of academic impact, for papers by Jeffrey M. Hausdorff
Rankless by CCL
2026