[HTML][HTML] Epileptic seizures detection using deep learning techniques: a review
A variety of screening approaches have been proposed to diagnose epileptic seizures,
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …
Handling of uncertainty in medical data using machine learning and probability theory techniques: A review of 30 years (1991–2020)
Understanding the data and reaching accurate conclusions are of paramount importance in
the present era of big data. Machine learning and probability theory methods have been …
the present era of big data. Machine learning and probability theory methods have been …
Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images
Abstract The coronavirus (COVID-19) is currently the most common contagious disease
which is prevalent all over the world. The main challenge of this disease is the primary …
which is prevalent all over the world. The main challenge of this disease is the primary …
Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991–2020
R Alizadehsani, A Khosravi, M Roshanzamir… - Computers in Biology …, 2021 - Elsevier
While coronary angiography is the gold standard diagnostic tool for coronary artery disease
(CAD), but it is associated with procedural risk, it is an invasive technique requiring arterial …
(CAD), but it is associated with procedural risk, it is an invasive technique requiring arterial …
Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …
Uncertainty-aware semi-supervised method using large unlabeled and limited labeled COVID-19 data
R Alizadehsani, D Sharifrazi, NH Izadi… - ACM Transactions on …, 2021 - dl.acm.org
The new coronavirus has caused more than one million deaths and continues to spread
rapidly. This virus targets the lungs, causing respiratory distress which can be mild or …
rapidly. This virus targets the lungs, causing respiratory distress which can be mild or …
Epileptic seizures detection in EEG signals using fusion handcrafted and deep learning features
Epilepsy is a brain disorder disease that affects people's quality of life.
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …
Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy …
A Shoeibi, N Ghassemi, M Khodatars, P Moridian… - Cognitive …, 2023 - Springer
Nowadays, many people worldwide suffer from brain disorders, and their health is in danger.
So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) and …
So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) and …
RLMD‐PA: a reinforcement learning‐based myocarditis diagnosis combined with a population‐based algorithm for pretraining weights
SV Moravvej, R Alizadehsani, S Khanam… - Contrast Media & …, 2022 - Wiley Online Library
Myocarditis is heart muscle inflammation that is becoming more prevalent these days,
especially with the prevalence of COVID‐19. Noninvasive imaging cardiac magnetic …
especially with the prevalence of COVID‐19. Noninvasive imaging cardiac magnetic …
Breast cancer dataset, classification and detection using deep learning
Incorporating scientific research into clinical practice via clinical informatics, which includes
genomics, proteomics, bioinformatics, and biostatistics, improves patients' treatment …
genomics, proteomics, bioinformatics, and biostatistics, improves patients' treatment …