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Toplam kayıt 8, listelenen: 1-8
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 ...
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 ...
Topological feature generation for link prediction in biological networks
(PEERJ INC, 2023)
Graph or network embedding is a powerful method for extracting missing or
potential information from interactions between nodes in biological networks. Graph
embedding methods learn representations of nodes and interactions ...
An empirical study of sentiment analysis utilizing machine learning and deep learning algorithms
(SPRINGER, 2023)
Among text-mining studies, one of the most studied topics is the text classifcation
task applied in various domains, including medicine, social media, and academia.
As a sub-problem in text classifcation, sentiment ...