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Toplam kayıt 14, listelenen: 1-10
Ensemble feature selection and classification methods for machine learning-based coronary artery disease diagnosis
(ELSEVIER, 2023)
Coronary artery disease (CAD) is a condition in which the heart is not fed sufficiently as a result of the accumulation of fatty matter. As reported by the World Health Organization, around 32% of the total deaths in the ...
PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach
(BMC, 2023)
BackgroundCell homeostasis relies on the concerted actions of genes, and dysregulated genes can lead to diseases. In living organisms, genes or their products do not act alone but within networks. Subsets of these networks ...
NeRNA: A negative data generation framework for machine learning applications of noncoding RNAs
(PERGAMON-ELSEVIER SCIENCE, 2023)
Many supervised machine learning based noncoding RNA (ncRNA) analysis methods have been developed to
classify and identify novel sequences. During such analysis, the positive learning datasets usually consist of
known ...
Machine learning approaches for underwater sensor network parameter prediction
(ELSEVIER, 2023)
Underwater Acoustic Sensor Networks (UASNs) have recently attracted scientists due to its wide range of real -world applications. However, there are design challenges in UASNs, such as limited network lifetime and low ...
Performance Analysis of Machine Learning and Bioinformatics Applications on High Performance Computing Systems
(Akademik Perspektif Derneği, 2020)
Nowadays, it is becoming increasingly important to use the most efficient and most suitable computational resources for algorithmic tools that extract meaningful information from big data and make smart decisions. In this ...
Microstructural, mechanical, tribological, and corrosion behavior of ultrafine bio-degradable Mg/CeO2 nanocomposites: Machine learning-based modeling and experiment
(ELSEVIER SCI LTD, 2023)
The present study investigated the microstructural, mechanical, tribological, and corrosion behavior of
near-dense and low-volume fraction magnesium-cerium dioxide (Mg/CeO2
) (x = 0.5, 1, and 1.5 vol.%)
nanocomposites ...
A comprehensive experimental and modeling study of the strain rate- and temperature-dependent deformation behavior of bio-degradable Mg-CeO2 nanocomposites
(ELSEVIER, 2024)
A comprehensive study was undertaken on the temperature-dependent and strain rate-sensitive deformation
behavior of near-dense low-volume fraction magnesium-cerium dioxide (Mg-CeO2
) nanocomposites synthesized
by powder ...
EdgeAISim: A toolkit for simulation and modelling of AI models in edge computing environments
(ELSEVIER, 2024)
To meet next-generation Internet of Things (IoT) application demands, edge computing moves processing power
and storage closer to the network edge to minimize latency and bandwidth utilization. Edge computing is
becoming ...
Comparative analysis of machine learning approaches for predicting respiratory virus infection and symptom severity
(PEERJ INC, 2023)
Respiratory diseases are among the major health problems causing a burden on hospitals. Diagnosis of infection and rapid prediction of severity without time-consuming clinical tests could be beneficial in preventing the ...
An efficient network intrusion detection approach based on logistic regression model and parallel artificial bee colony algorithm
(ELSEVIER, 2024)
In recent years, the widespread use of the Internet has created many issues, especially in the area of cybersecurity. It is critical to detect intrusions in network traffic, and researchers have developed network intrusion ...