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Toplam kayıt 48, listelenen: 1-10
Compressed spectrum sensing using sparse recovery convergence patterns through machine learning classification
(Institute of Electrical and Electronics Engineers Inc., 2019)
Despite the well-known success of sub-Nyquist sampling in reducing the hardware and computational costs of spectrum sensing, it still has the shortcoming of requiring a pre-determined spectrum sparsity level. This paper ...
Selection of waveform parameters using machine learning for 5G and beyond
(Institute of Electrical and Electronics Engineers Inc., 2019)
Flexibility is one of the essential requirements for future cellular communications technologies. Providing customized communications solutions for each user and service type cannot be possible without the flexibility in ...
Detecting spam tweets using machine learning and effective preprocessing
(Association for Computing Machinery, Inc, 2021)
Nowadays, with the rapid increase in popularity of online social networks (OSNs), these platforms are realized as ideal places for spammers. Unfortunately, these spammers can easily publish malicious content, advertise ...
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 ...
Application of machine learning and medical imaging in the detection of COVID-19 patients: A review article
(Wolters Kluwer Medknow Publications, 2022)
In the present study, a particular technique of artificial intelligence (AI) is applied for diagnosis and classifying medical images of patients with coronavirus disease (COVID-19). Chest radiography and laboratory-based ...
How is the stock exchange index affected by the disclosures of politicians?
(Springer Science and Business Media Deutschland GmbH, 2021)
The main purpose of this study is to understand the main influence of the politicians’ disclosure on the stock exchange index. In this context, a machine learning model is built in order to understand the hidden patterns ...
Prediction of general anxiety disorder using machine learning techniques
(Nova Science Publishers, Inc., 2022)
Today, the increase in mental health problems, the variable nature of mental health and the lack of sufficient number of mental health professionals have led to the search for machine learning that applied to mental health ...
Screening for Alzheimer's disease using prefrontal resting-state functional near-infrared spectroscopy
(Frontiers Media S.A., 2022)
IntroductionAlzheimer's disease (AD) is neurodegenerative dementia that causes neurovascular dysfunction and cognitive impairment. Currently, 50 million people live with dementia worldwide, and there are nearly 10 million ...
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 ...
A multi-spectral myelin annotation tool for machine learning based myelin quantification [version 1; peer review: 1 not approved]
(F1000 Research Ltd, 2021)
Myelin is an essential component of the nervous system and myelin damage causes demyelination diseases. Myelin is a sheet of oligodendrocyte membrane wrapped around the neuronal axon. In the fluorescent images, experts ...