Search Results - "Rajendra Acharya, U."

SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach by Mousavi, Sajad, Afghah, Fatemeh, Acharya, U Rajendra

“…Electroencephalogram (EEG) is a common base signal used to monitor brain activities and diagnose sleep disorders. Manual sleep stage scoring is a…”
Get full text

A new approach to characterize epileptic seizures using analytic time-frequency flexible wavelet transform and fractal dimension by Sharma, Manish, Pachori, Ram Bilas, Rajendra Acharya, U.

“…•A new automated model for epileptic seizure detection.•The model employs a combination of recently introduced analytic time-frequency flexible wavelet…”
Get full text

Automated detection of COVID-19 cases using deep neural networks with X-ray images by Ozturk, Tulin, Talo, Muhammed, Yildirim, Eylul Azra, Baloglu, Ulas Baran, Yildirim, Ozal, Rajendra Acharya, U.

“…The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of China in December 2019, spread rapidly around the world and became a pandemic…”
Get full text

Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals by Michielli, Nicola, Acharya, U. Rajendra, Molinari, Filippo

“…Automated evaluation of a subject's neurocognitive performance (NCP) is a relevant topic in neurological and clinical studies. NCP represents the…”
Get full text

Automated arrhythmia detection using novel hexadecimal local pattern and multilevel wavelet transform with ECG signals by Tuncer, Turker, Dogan, Sengul, Pławiak, Paweł, Rajendra Acharya, U.

“…Electrocardiography (ECG) is widely used for arrhythmia detection nowadays. The machine learning methods with signal processing algorithms have been used for…”
Get full text

Application of deep transfer learning for automated brain abnormality classification using MR images by Talo, Muhammed, Baloglu, Ulas Baran, Yıldırım, Özal, Rajendra Acharya, U

“…•MR brain images are classified using a pre-trained model and deep transfer learning techniques.•The proposed model yields 5-fold classification accuracy of…”
Get full text

Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks by Ardakani, Ali Abbasian, Kanafi, Alireza Rajabzadeh, Acharya, U. Rajendra, Khadem, Nazanin, Mohammadi, Afshin

“…Fast diagnostic methods can control and prevent the spread of pandemic diseases like coronavirus disease 2019 (COVID-19) and assist physicians to better manage…”
Get full text

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals by Acharya, U. Rajendra, Oh, Shu Lih, Hagiwara, Yuki, Tan, Jen Hong, Adeli, Hojjat

“…An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical…”
Get full text

Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring by Pławiak, Paweł, Abdar, Moloud, Rajendra Acharya, U.

“…In the recent decades, credit scoring has become a very important analytical resource for researchers and financial institutions around the world. It helps to…”
Get full text

Deep learning for healthcare applications based on physiological signals: A review by Faust, Oliver, Hagiwara, Yuki, Hong, Tan Jen, Lih, Oh Shu, Acharya, U Rajendra

“…•Importance: In 2017 the number of publications on deep learning for physiological signal analysis increased significantly. Indeed, 2017 saw more papers…”
Get full text

HAN-ECG: An interpretable atrial fibrillation detection model using hierarchical attention networks by Mousavi, Sajad, Afghah, Fatemeh, Acharya, U. Rajendra

“…Atrial fibrillation (AF) is one of the most prevalent cardiac arrhythmias that affects the lives of many people around the world and is associated with a…”
Get full text

Automatic Sleep-Stage Scoring in Healthy and Sleep Disorder Patients Using Optimal Wavelet Filter Bank Technique with EEG Signals by Sharma, Manish, Tiwari, Jainendra, Acharya, U Rajendra

“…Sleep stage classification plays a pivotal role in effective diagnosis and treatment of sleep related disorders. Traditionally, sleep scoring is done manually…”
Get full text

Automated EEG-based screening of depression using deep convolutional neural network by Acharya, U. Rajendra, Oh, Shu Lih, Hagiwara, Yuki, Tan, Jen Hong, Adeli, Hojjat, Subha, D. P

“…•Classification of normal and depression using EEG signals.•Employed a 13-layer deep convolutional neural network model.•Minimum hand-crafted features required…”
Get full text

Tetromino pattern based accurate EEG emotion classification model by Tuncer, Turker, Dogan, Sengul, Baygin, Mehmet, Rajendra Acharya, U.

“…Nowadays, emotion recognition using electroencephalogram (EEG) signals is becoming a hot research topic. The aim of this paper is to classify emotions of EEG…”
Get full text

Application of artificial intelligence in wearable devices: Opportunities and challenges by Nahavandi, Darius, Alizadehsani, Roohallah, Khosravi, Abbas, Acharya, U Rajendra

“…: Wearable technologies have added completely new and fast emerging tools to the popular field of personal gadgets. Aside from being fashionable and equipped…”
Get full text

Deep convolution neural network for accurate diagnosis of glaucoma using digital fundus images by Raghavendra, U, Fujita, Hamido, Bhandary, Sulatha V, Gudigar, Anjan, Tan, Jen Hong, Acharya, U Rajendra

“…•An eighteen layer CNN framework is proposed for glaucoma diagnosis.•Used 1426 fundus images (normal: 589 and glaucoma: 837).•Attained accuracy of 98.13%,…”
Get full text

A new approach for arrhythmia classification using deep coded features and LSTM networks by Yildirim, Ozal, Baloglu, Ulas Baran, Tan, Ru-San, Ciaccio, Edward J., Acharya, U. Rajendra

“…•High performance classification of arrhythmia types with LSTM and CAE-LSTM based structures.•Signal sizes of arrhythmic beats are reduced by convolutional…”
Get full text

A Deep Learning Model for Automated Sleep Stages Classification Using PSG Signals by Yildirim, Ozal, Baloglu, Ulas Baran, Acharya, U Rajendra

“…Sleep disorder is a symptom of many neurological diseases that may significantly affect the quality of daily life. Traditional methods are time-consuming and…”
Get full text

A novel Parkinson’s Disease Diagnosis Index using higher-order spectra features in EEG signals by Yuvaraj, Rajamanickam, Rajendra Acharya, U., Hagiwara, Yuki

“…Higher-order spectra (HOS) is an efficient feature extraction method used in various biomedical applications such as stages of sleep, epilepsy detection,…”
Get full text

A novel automated diagnostic system for classification of myocardial infarction ECG signals using an optimal biorthogonal filter bank by Sharma, Manish, Tan, Ru San, Acharya, U. Rajendra

“…Myocardial infarction (MI), also referred to as heart attack, occurs when there is an interruption of blood flow to parts of the heart, due to the acute…”
Get full text