Artificial intelligence techniques for automated diagnosis of neurological disorders
Background: Authors have been advocating the research ideology that a computer-aided
diagnosis (CAD) system trained using lots of patient data and physiological signals and …
diagnosis (CAD) system trained using lots of patient data and physiological signals and …
A review on computer aided diagnosis of acute brain stroke
Amongst the most common causes of death globally, stroke is one of top three affecting over
100 million people worldwide annually. There are two classes of stroke, namely ischemic …
100 million people worldwide annually. There are two classes of stroke, namely ischemic …
Automated detection of schizophrenia using nonlinear signal processing methods
Examination of the brain's condition with the Electroencephalogram (EEG) can be helpful to
predict abnormality and cerebral activities. The purpose of this study was to develop an …
predict abnormality and cerebral activities. The purpose of this study was to develop an …
Fusion of multivariate EEG signals for schizophrenia detection using CNN and machine learning techniques
Schizophrenia is a severe mental disorder that has adverse effects on the behavior of an
individual such as disorganized speech and delusions. Electroencephalography (EEG) …
individual such as disorganized speech and delusions. Electroencephalography (EEG) …
Random forest-based prediction of stroke outcome
We research into the clinical, biochemical and neuroimaging factors associated with the
outcome of stroke patients to generate a predictive model using machine learning …
outcome of stroke patients to generate a predictive model using machine learning …
Automated detection of schizophrenia using optimal wavelet-based norm features extracted from single-channel EEG
M Sharma, UR Acharya - Cognitive Neurodynamics, 2021 - Springer
Schizophrenia (SZ) is a mental disorder, which affects the ability of human thinking, memory,
and way of living. Manual screening of SZ patients is tedious, laborious and prone to human …
and way of living. Manual screening of SZ patients is tedious, laborious and prone to human …
[PDF][PDF] Evaluation and classification of the brain tumor MRI using machine learning technique
The proposed work implements a Machine-Learning-Technique (MLT) to evaluate and
classify the tumor regions into low/high grade based on the analysis carriedout with the …
classify the tumor regions into low/high grade based on the analysis carriedout with the …
A deep supervised approach for ischemic lesion segmentation from multimodal MRI using Fully Convolutional Network
The principle restorative step in the treatment of ischemic stroke depends on how fast the
lesion is delineated from the Magnetic Resonance Imaging (MRI) images. This will serve as …
lesion is delineated from the Magnetic Resonance Imaging (MRI) images. This will serve as …
Deep transfer learning for automatic prediction of hemorrhagic stroke on CT images
BN Rao, S Mohanty, K Sen, UR Acharya… - … Methods in Medicine, 2022 - Wiley Online Library
Intracerebral hemorrhage (ICH) is the most common type of hemorrhagic stroke which
occurs due to ruptures of weakened blood vessel in brain tissue. It is a serious medical …
occurs due to ruptures of weakened blood vessel in brain tissue. It is a serious medical …
An innovative methodology for the determination of wind farms installation location characteristics using GIS and Delaunay Triangulation
Renewable energy development and more specifically Wind Farm (WF) installation has
been increased during the last years by most countries. A discipline that has been studied …
been increased during the last years by most countries. A discipline that has been studied …