Acharya, U. Rajendra

A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Abdar, M., Pourpanah, F., Hussain, S., Rezazadegan, D., Liu, L., Ghavamzadeh, M., Fieguth, P., Cao, X., Khosravi, A., Acharya, U. R., et al. (2021) · Information Fusion

Adversarial Robustness in Machine LearningGaussian Processes and Bayesian Inference

Cited by 3,111

Application of explainable artificial intelligence for healthcare: a systematic review of the last decade (2011-2022)

Loh, H. W., Ooi, C. P., Seoni, S., Barua, P. D., Molinari, F., & Acharya, U. R. (2022) · Computer Methods and Programs in Biomedicine

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 734

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

Martis, R. J., Acharya, U. R., & Min, L. C. (2013) · Biomedical Signal Processing and Control

ECG Monitoring and AnalysisCardiac electrophysiology and arrhythmias

Cited by 722

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

Acharya, U. R., Oh, S. L., Hagiwara, Y., Tan, J. H., Adeli, H., & Subha, D. P. (2018) · Computer Methods and Programs in Biomedicine

EEG and Brain-Computer InterfacesEmotion and Mood Recognition

Cited by 650

Convolutional neural networks for multi-class brain disease detection using MRI images

Talo, M., Yildirim, O., Baloglu, U. B., Aydin, G., & Acharya, U. R. (2019) · Computerized Medical Imaging and Graphics

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 301

Artificial Intelligence Enabled Personalised Assistive Tools to Enhance Education of Children with Neurodevelopmental Disorders—A Review

Barua, P. D., Vicnesh, J., Gururajan, R., Oh, S. L., Palmer, E., Azizan, M. M., Kadri, N. A., & Acharya, U. R. (2022) · International Journal of Environmental Research and Public Health

Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive Learning

Cited by 270

Emotion recognition in EEG signals using deep learning methods: A review

Jafari, M., Shoeibi, A., Khodatars, M., Bagherzadeh, S., Shalbaf, A., García, D. L., Gorriz, J. M., & Acharya, U. R. (2023) · Computers in Biology and Medicine

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 240

Application of uncertainty quantification to artificial intelligence in healthcare: A review of last decade (2013–2023)

Seoni, S., Jahmunah, V., Salvi, M., Barua, P. D., Molinari, F., & Acharya, U. R. (2023) · Computers in Biology and Medicine

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 239

Computer-based detection of diabetes retinopathy stages using digital fundus images

Acharya, U. R., Lim, C. M., Ng, E. Y. K., Chee, C., & Tamura, T. (2009) · Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 217

Designing interpretable ML system to enhance trust in healthcare: A systematic review to proposed responsible clinician-AI-collaboration framework

Nasarian, E., Alizadehsani, R., Acharya, U. R., & Tsui, K.-L. (2024) · Information Fusion

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 207

Artificial Intelligence Techniques for Automated Diagnosis of Neurological Disorders

Raghavendra, U., Acharya, U. R., & Adeli, H. (2019) · European Neurology

Artificial Intelligence in HealthcareEEG and Brain-Computer Interfaces

Cited by 174

Automated emotion recognition: Current trends and future perspectives

Maithri, M., Raghavendra, U., Gudigar, A., Samanth, J., Barua, P. D., Murugappan, M., Chakole, Y., & Acharya, U. R. (2022) · Computer Methods and Programs in Biomedicine

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 172

GaborPDNet: gabor transformation and deep neural network for Parkinson's disease detection using EEG signals

Loh, H. W., Ooi, C. P., Palmer, E., Barua, P. D., Dogan, S., Tuncer, T., Baygin, M., & Acharya, U. R. (2021) · Electronics

EEG and Brain-Computer InterfacesArtificial Intelligence in Healthcare

Cited by 144

Multi-modality approaches for medical support systems: A systematic review of the last decade

Salvi, M., Loh, H. W., Seoni, S., Barua, P. D., García, S., Molinari, F., & Acharya, U. R. (2024) · Information Fusion

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 144

Drosophila Sirt2/mammalian SIRT3 deacetylates ATP synthase β and regulates complex V activity

Rahman, M., Nirala, N. K., Singh, A., Zhu, L. J., Taguchi, K., Bamba, T., Fukusaki, E., Shaw, L. M., Lambright, D. G., Acharya, J. K., et al. (2014) · Journal of Cell Biology

Sirtuins and Resveratrol in MedicineATP Synthase and ATPases Research

Cited by 116

A novel genetic algorithm based system for the scheduling of medical treatments

Squires, M., Tao, X., Elangovan, S., Gururajan, R., Zhou, X., & Acharya, U. R. (2022) · Expert Systems with Applications

Healthcare Operations and Scheduling OptimizationScheduling and Optimization Algorithms

Cited by 110

The need for quantification of uncertainty in artificial intelligence for clinical data analysis: increasing the level of trust in the decision-making process

Abdar, M., Khosravi, A., Islam, S. M. S., Acharya, U. R., & Vasilakos, A. V. (2022) · IEEE Systems, Man, and Cybernetics Magazine

Artificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)

Cited by 55

Artificial intelligence for early detection of diabetes mellitus complications via retinal imaging

Sobhi, N., Sadeghi-Bazargani, Y., Mirzaei, M., Abdollahi, M., Jafarizadeh, A., Pedrammehr, S., Alizadehsani, R., Tan, R.-S., Islam, S. M. S., & Acharya, U. R. (2025) · Journal of Diabetes & Metabolic Disorders

Retinal Imaging and AnalysisArtificial Intelligence in Healthcare

Cited by 39

PFP-LHCINCA: Pyramidal Fixed-Size Patch-Based Feature Extraction and Chi-Square Iterative Neighborhood Component Analysis for Automated Fetal Sex Classification on Ultrasound Images

Kaplan, E., Ekinci, T., Kaplan, S., Barua, P. D., Dogan, S., Tuncer, T., Tan, R.-S., Arunkumar, N., & Acharya, U. R. (2022) · Contrast Media & Molecular Imaging

Image Retrieval and Classification TechniquesArtificial Intelligence in Healthcare

Cited by 16