Applications of machine learning to diagnosis and treatment of neurodegenerative diseases
MA Myszczynska, PN Ojamies, AMB Lacoste… - Nature reviews …, 2020 - nature.com
Globally, there is a huge unmet need for effective treatments for neurodegenerative
diseases. The complexity of the molecular mechanisms underlying neuronal degeneration …
diseases. The complexity of the molecular mechanisms underlying neuronal degeneration …
Understanding artificial intelligence experience: A customer perspective
The engagement between customers and brands is being transformed by artificial
intelligence (AI). However, there has been little study into AI-powered customer experiences; …
intelligence (AI). However, there has been little study into AI-powered customer experiences; …
Single slice based detection for Alzheimer's disease via wavelet entropy and multilayer perceptron trained by biogeography-based optimization
Detection of Alzheimer's disease (AD) from magnetic resonance images can help
neuroradiologists to make decision rapidly and avoid missing slight lesions in the brain …
neuroradiologists to make decision rapidly and avoid missing slight lesions in the brain …
Global research on artificial intelligence-enhanced human electroencephalogram analysis
The application of artificial intelligence (AI) technologies in assisting human
electroencephalogram (EEG) analysis has become an active scientific field. This study aims …
electroencephalogram (EEG) analysis has become an active scientific field. This study aims …
[HTML][HTML] Eye fatigue estimation using blink detection based on Eye Aspect Ratio Mapping (EARM)
A Kuwahara, K Nishikawa, R Hirakawa, H Kawano… - Cognitive Robotics, 2022 - Elsevier
With the advent of the information society, the eyes' health is threatened all over the world.
Rules and systems have been proposed to avoid these problems, but most users do not use …
Rules and systems have been proposed to avoid these problems, but most users do not use …
Smart pathological brain detection by synthetic minority oversampling technique, extreme learning machine, and Jaya algorithm
YD Zhang, G Zhao, J Sun, X Wu, ZH Wang… - Multimedia Tools and …, 2018 - Springer
Pathological brain detection is an automated computer-aided diagnosis for brain images.
This study provides a novel method to achieve this goal. We first used synthetic minority …
This study provides a novel method to achieve this goal. We first used synthetic minority …
Automated diagnosis of multi-class brain abnormalities using MRI images: a deep convolutional neural network based method
Automated detection of multi-class brain abnormalities through magnetic resonance imaging
(MRI) has received much attention due to its clinical significance and therefore has become …
(MRI) has received much attention due to its clinical significance and therefore has become …
A hybrid feature extraction approach for brain MRI classification based on Bag-of-words
Magnetic resonance imaging (MRI) has attracted considerable attention in medical
engineering community, since it is a non-invasive diagnostic technique and for its …
engineering community, since it is a non-invasive diagnostic technique and for its …
A deep stacked random vector functional link network autoencoder for diagnosis of brain abnormalities and breast cancer
Automated diagnosis of two-class brain abnormalities through magnetic resonance imaging
(MRI) has progressed significantly in past few years. In contrast, there exists a limited …
(MRI) has progressed significantly in past few years. In contrast, there exists a limited …
A pathological brain detection system based on extreme learning machine optimized by bat algorithm
Aim: It is beneficial to classify brain images as healthy or pathological automatically,
because 3D brain images can generate so much information which is time consuming and …
because 3D brain images can generate so much information which is time consuming and …