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September 18, 2024JACC. Cardiovascular imaging15 citationsOpen Access

Deep Learning Model of Diastolic Dysfunction Risk Stratifies the Progression of Early-Stage Aortic Stenosis

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MTMárton TokodiRSRohan ShahAJAnkush D. Jamthikar

Key Result

Deep learning assessment of diastolic dysfunction can stratify the risk of progression in early-stage aortic stenosis.

Structured PICO

Does assessment of diastolic dysfunction using a deep learning model stratify the risk of progression in patients with early-stage aortic stenosis?

P
Population
Patients with early-stage aortic stenosis
I
Intervention
Deep learning (DL) model assessment of diastolic dysfunction (DD)
O
Outcome
Progression of early-stage aortic stenosis

A deep learning model assessing diastolic dysfunction can help stratify the risk of progression in patients with early-stage aortic stenosis.

Abstract

Assessment of DD using DL can stratify the latent risk associated with the progression of early-stage AS.

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Cite This Study

Tokodi et al. (2024) studied this question. Deep learning assessment of diastolic dysfunction can stratify the risk of progression in early-stage aortic stenosis.

synapsesocial.com/papers/696f02702c0018714d31bec4https://doi.org/10.1016/j.jcmg.2024.07.017
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