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Toplam kayıt 15, listelenen: 1-10
Multi fragment melting analysis system (MFMAS) for one-step identification of lactobacilli
(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2020)
The accurate identification of lactobacilli is essential for the effective management of industrial practices associated with lactobacilli strains, such as the production of fermented foods or probiotic supplements. For ...
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 ...
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 ...
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 ...
SVM-RCE-R-OPT: Optimization of Scoring Function for SVM-RCE-R
(SPRINGER INTERNATIONAL PUBLISHING AGGEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, 2021)
Gene expression data classification provides a challenge in classification due to it having high dimensionality and a relatively small sample size. Different feature selection approaches have been used to overcome this ...
CoviDetector: A transfer learning-based semi supervised approach to detect Covid-19 using CXR images
(ELSEVIER, 2023)
COVID-19 was one of the deadliest and most infectious illnesses of this century. Research has been done to
decrease pandemic deaths and slow down its spread. COVID-19 detection investigations have utilised Chest
X-ray ...