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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 ...
Automated quantification of immunomagnetic beads and leukemia cells from optical microscope images
(ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 2019)
Quantification of tumor cells is crucial for early detection and monitoring the progress of cancer. Several methods have been developed for detecting tumor cells. However, automated quantification of cells in the presence ...
Automated processing and classification of medical thermal images
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2022)
The aim of this dissertation is to develop computer aided methods for processing
and evaluating medical infrared thermal images. Throughout this study three problems
were evaluated. The first problem was to automatically ...
Machine and deep learning based analysis of tumors on FDG-PET images
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2022)
Analysis of a tumor is essential in treatment planning and evaluation of treatment response. Positron Emission Tomography (PET) is a vital imaging device for clinical oncology in understanding the metabolic structure of ...
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 ...
