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Toplam kayıt 12, listelenen: 1-10
Advances in quantitative analysis of astrocytes using machine learning
(Wolters Kluwer Medknow Publications, 2023)
Astrocytes, a subtype of glial cells, are starshaped cells that are involved in the homeostasis and blood flow control of the central nervous system (CNS). They are known to provide structural and functional support to ...
Predicting the effects of repetitive transcranial magnetic stimulation on cognitive functions in patients with alzheimer's disease by automated EEG analysis
(Frontiers Media SA, 2022)
Alzheimer's disease (AD) is a progressive, neurodegenerative brain disorder that generally affects the elderly. Today, after the limited benefit of the pharmacological treatment strategies, numerous noninvasive brain ...
Predicting path loss distribution of an area from satellite ımages using deep learning
(IEEE - Institute of Electrical and Electronics Engineers, Inc., 2020)
Path loss prediction is essential for network planning in any wireless communication system. For cellular networks, it is usually achieved through extensive received signal power measurements in the target area. When the ...
Fuzzy classification methods based diagnosis of Parkinson’s disease from speech test cases
(Bentham Science Publishers, 2019)
Background: Together with the Alzheimer’s disease, Parkinson’s disease is considered as one of the two serious known neurodegenerative diseases. Physicians find it hard to predict whether a given patient has already developed ...
SNF-CVAE: Computational method to predict drug-disease interactions using similarity network fusion and collective variational autoencoder
(Elsevier, 2021)
Drug repositioning is an emerging approach to identify novel therapeutic potentials for approved drugs and discover therapies for previously untreatable diseases. Drug repositioning has also attracted considerable attention ...
A review of computational drug repositioning: Strategies, approaches, opportunities, challenges, and directions
(BMC, 2020)
Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an important role in optimizing the ...
Modeling traders' behavior with deep learning and machine learning methods: Evidence from BIST 100 index
(Wiley-Hindawi, 2020)
Although the vast majority of fundamental analysts believe that technical analysts' estimates and technical indicators used in these analyses are unresponsive, recent research has revealed that both professionals and ...
SNF-NN: Computational method to predict drug-disease interactions using similarity network fusion and neural networks
(BioMed Central Ltd., 2021)
Background: Drug repositioning is an emerging approach in pharmaceutical research for identifying novel therapeutic potentials for approved drugs and discover therapies for untreated diseases. Due to its time and cost ...
An efficient approach to predict eye diseases from symptoms using machine learning and ranker-based feature selection methods
(MDPI, 2023)
The eye is generally considered to be the most important sensory organ of humans. Diseases and other degenerative conditions of the eye are therefore of great concern as they affect the function of this vital organ. With ...
A survey of machine learning-based methods for COVID-19 medical image analysis
(Springer Science and Business Media Deutschland GmbH, 2023)
The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected after only 30 months since the first occurrences of the disease in December ...