Gray Level Co-Occurrence Matrix, Fractal and Wavelet Analyses of Discrete Changes in Cell Nuclear Structure following Osmotic Stress: Focus on Machine Learning Methods

In this work, we demonstrate that it is possible to create supervised machine-learning models using a support vector machine and random forest algorithms to separate yeast cells exposed to hyperosmotic stress from intact cells. We performed fractal, gray level co-occurrence matrix (GLCM), and discre...

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Detaylı Bibliyografya
Asıl Yazarlar:	Igor Pantic, Svetlana Valjarevic, Jelena Cumic, Ivana Paunkovic, Tatjana Terzic, Peter R. Corridon
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	MDPI AG 2023-03-01
Seri Bilgileri:	Fractal and Fractional
Konular:	cell signal analysis nucleus stress supervised learning
Online Erişim:	https://www.mdpi.com/2504-3110/7/3/272
Etiketler:	Etiketle Etiket eklenmemiş, İlk siz ekleyin!

Gray Level Co-Occurrence Matrix, Fractal and Wavelet Analyses of Discrete Changes in Cell Nuclear Structure following Osmotic Stress: Focus on Machine Learning Methods

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