Correction: A new integrated machine learning model: application to improve the accuracy of predicting left atrial appendage thrombus in patients with non-valvular atrial fibrillation

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Publication Details

Journal
Frontiers in Medicine
Published
2025-10-14
DOI
https://doi.org/10.3389/fmed.2025.1718394
Primary Topic
Atrial Fibrillation Management and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
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article

Correction: A new integrated machine learning model: application to improve the accuracy of predicting left atrial appendage thrombus in patients with non-valvular atrial fibrillation

Frontiers in Medicine
Atrial Fibrillation Management and Outcomes
article

Correction: A new integrated machine learning model: application to improve the accuracy of predicting left atrial appendage thrombus in patients with non-valvular atrial fibrillation

article en

Abstract

No abstract available for this paper.
Frontiers in MedicineVol. 12
Médecins Sans Frontières (CH)
Openalex Percentile: Top 56%
Atrial Fibrillation Management and Outcomes
DOIOpen Access PDFOpenAlex
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Correction: A new integrated machine learning model: application to improve the accuracy of predicting left atrial appendage thrombus in patients with non-valvular atrial fibrillation · Frontiers in Medicine (2025) | TGRS Research Map | TGRS