Machine Learning–Based Integration of Plasma Lipidomes and Clinical Variables for Predicting Atrial Fibrosis in Atrial Fibrillation
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ABSTRACT: Atrial fibrosis is a major arrhythmogenic substrate in atrial fibrillation (AF), but its non-invasive identification remains limited. We aimed to characterize the plasma lipidomic signature of atrial fibrosis in patients with AF and to develop an integrated predictive model combining lipidomic and clinical features.
ORGANISM(S): Homo Sapiens
SUBMITTER:
Ming Chu
PROVIDER: PXD076658 | iProX | Mon Apr 06 00:00:00 BST 2026
REPOSITORIES: iProX
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