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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 ...
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 ...
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 ...
How to engage consumers through effective social media use-guidelines for consumer goods companies from an emerging market
(Universidad de Talca, 2021)
This study aims to establish actionable guidelines and provide strategic insights as a means of increasing the social media effectiveness of consumer brands. Post-related factors in addition to the contextual and temporal ...
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 ...
Data analysis in health and big data: A machine learning medical diagnosis model based on patients’ complaints
(Taylor and Francis Inc., 2021)
The emergence of big data made it possible to make better predictions and discover hidden patterns which contain a load of useful information. Like other domains, health discipline is also enjoying this new data science ...
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 ...
Classification of patients with alzheimer's disease and dementia with lewy bodies using resting EEG selected features at sensor and source levels: A proof-of-concept study
(Bentham Science, 2021)
Background: Early differentiation between Alzheimer's disease (AD) and Dementia with Lewy Bodies (DLB) is important for accurate prognosis, as DLB patients typically show faster disease progression. Cortical neural networks, ...
Blind signal analysis
(Wiley, 2021)
Blind signal analysis (BSA) plays an essential role in wireless communication when the receiver does not know most or all of the received signal parameters. This chapter provides an in-depth understanding of BSA with ...