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Automatic Classification of Coronary Stenosis Using Feature Selection and a Hybrid Evolutionary Algorithm

In this paper, a novel method for the automatic classification of coronary stenosis based on a feature selection strategy driven by a hybrid evolutionary algorithm is proposed. The main contribution is the characterization of the coronary stenosis anomaly based on the automatic selection of an effic...

Täydet tiedot

Tallennettuna:
Päätekijät: Miguel-Angel Gil-Rios, Claire Chalopin, Ivan Cruz-Aceves, Juan-Manuel Lopez-Hernandez, Martha-Alicia Hernandez-Gonzalez, Sergio-Eduardo Solorio-Meza
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: MDPI AG 2023-05-01
Sarja:Axioms
Aiheet:
Boltzmann distribution
coronary angiograms
feature selection
simulated annealing
stenosis classification
support vector machine
Linkit:https://www.mdpi.com/2075-1680/12/5/462
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