Unsupervised Clustering of Patients Undergoing Thoracoscopic Ablation Identifies Relevant Phenotypes for Advanced Atrial Fibrillation

<b>Background/Objectives</b>: The rate of recurrence after ablation for atrial fibrillation (AF) is considerable. Risk stratification for AF recurrence after ablation remains incompletely developed. Unsupervised clustering is a machine learning technique which might provide valuable insights in AF r...

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Ngā kaituhi matua:	Ilse Meijer, Marc M. Terpstra, Oscar Camara, Henk A. Marquering, Nerea Arrarte Terreros, Joris R. de Groot
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	MDPI AG 2025-05-01
Rangatū:	Diagnostics
Ngā marau:	unsupervised machine learning principal component analysis K-Means thoracoscopic ablation atrial fibrillation phenotyping
Urunga tuihono:	https://www.mdpi.com/2075-4418/15/10/1269
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!