Multiple sclerosis detection based on biorthogonal wavelet transform, RBF kernel principal component analysis, and logistic regression
To detect multiple sclerosis (MS) diseases early, we proposed a novel method on the
hardware of magnetic resonance imaging, and on the software of three successful methods …
hardware of magnetic resonance imaging, and on the software of three successful methods …
Comparison of machine learning methods for stationary wavelet entropy-based multiple sclerosis detection: decision tree, k-nearest neighbors, and support vector …
In order to detect multiple sclerosis (MS) subjects from healthy controls (HCs) in magnetic
resonance imaging, we developed a new system based on machine learning. The MS …
resonance imaging, we developed a new system based on machine learning. The MS …
Imaging as a (pre) clinical tool in parasitology
CM de Korne, L van Lieshout, FWB van Leeuwen… - Trends in …, 2023 - cell.com
Imaging of parasites is central to diagnosis of many parasitic diseases and has thus far
played an important role in the development of antiparasitic strategies. The development of …
played an important role in the development of antiparasitic strategies. The development of …
Benefits of artificial intelligence in medicine
S Yeasmin - 2019 2nd International Conference on Computer …, 2019 - ieeexplore.ieee.org
Artificial intelligence is one of the most discussed topics of the present time. The burning
question of today about artificial intelligence is “will it be beneficial or dangerous for a …
question of today about artificial intelligence is “will it be beneficial or dangerous for a …
Deep learning application to clinical decision support system in sleep stage classification
Recently, deep learning for automated sleep stage classification has been introduced with
promising results. However, as many challenges impede their routine application, automatic …
promising results. However, as many challenges impede their routine application, automatic …
Model-driven decision making in multiple sclerosis research: existing works and latest trends
R Alshamrani, A Althbiti, Y Alshamrani, F Alkomah… - Patterns, 2020 - cell.com
Multiple sclerosis (MS) is a neurological disorder that strikes the central nervous system.
Due to the complexity of this disease, healthcare sectors are increasingly in need of shared …
Due to the complexity of this disease, healthcare sectors are increasingly in need of shared …
Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection
Objectives Widespread implementation of electronic databases has improved the
accessibility of plaintext clinical information for supplementary use. Numerous machine …
accessibility of plaintext clinical information for supplementary use. Numerous machine …
[PDF][PDF] Artificial intelligence in medicine: humans need not apply?
Artificial intelligence (AI) is a rapidly growing field with a wide range of applications. Driven
by economic constraints and the potential to reduce human error, we believe that over the …
by economic constraints and the potential to reduce human error, we believe that over the …
Electronic Devices in the Artificial Intelligence of the Internet of Medical Things (AIoMT)
The current medical diseases and infections necessitate advanced medical equipment
(medical devices) to bridge the gap between existing and predictable diseases. This has …
(medical devices) to bridge the gap between existing and predictable diseases. This has …
Classification of single-channel EEG signals for epileptic seizures detection based on hybrid features
Y Lu, Y Ma, C Chen, Y Wang - Technology and Health Care, 2018 - content.iospress.com
BACKGROUND: Epilepsy is a common chronic neurological disorder of the brain. Clinically,
epileptic seizures are usually detected via the continuous monitoring of …
epileptic seizures are usually detected via the continuous monitoring of …