A Machine Learning Challenge: Detection of Cardiac Amyloidosis Based on Bi-Atrial and Right Ventricular Strain and Cardiac Function

Background: This study challenges state-of-the-art cardiac amyloidosis (CA) diagnostics by feeding multi-chamber strain and cardiac function into supervised machine (SVM) learning algorithms. Methods: Forty-three CA (32 males; 79 years (IQR 71; 85)), 20 patients with hypertrophic cardiomyopathy (HCM...

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Detalles Bibliográficos
Autores principales: Eckstein, Jan, Moghadasi, Negin, Körperich, Hermann, Weise Valdés, Elena, Sciacca, Vanessa, Paluszkiewicz, Lech, Burchert, Wolfgang, Piran, Misagh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689404/
https://www.ncbi.nlm.nih.gov/pubmed/36359536
http://dx.doi.org/10.3390/diagnostics12112693

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689404/
https://www.ncbi.nlm.nih.gov/pubmed/36359536
http://dx.doi.org/10.3390/diagnostics12112693

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