AIMC Topic: Myocarditis
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Deep learning automatically distinguishes myocarditis patients from normal subjects based on MRI.
The international journal of cardiovascular imaging
Nov 7, 2024
Myocarditis, characterized by inflammation of the myocardial tissue, presents substantial risks to cardiovascular functionality, potentially precipitating critical outcomes including heart failure and arrhythmias. This investigation primarily aims to...
Deep Learning Virtual Contrast-Enhanced T1 Mapping for Contrast-Free Myocardial Extracellular Volume Assessment.
Journal of the American Heart Association
Sep 30, 2024
BACKGROUND: The acquisition of contrast-enhanced T1 maps to calculate extracellular volume (ECV) requires contrast agent administration and is time consuming. This study investigates generative adversarial networks for contrast-free, virtual extracel...
Artificial intelligence and myocarditis-a systematic review of current applications.
Heart failure reviews
Aug 14, 2024
Myocarditis, marked by heart muscle inflammation, poses significant clinical challenges. This study, guided by PRISMA guidelines, explores the expanding role of artificial intelligence (AI) in myocarditis, aiming to consolidate current knowledge and ...
ELRL-MD: a deep learning approach for myocarditis diagnosis using cardiac magnetic resonance images with ensemble and reinforcement learning integration.
Physiological measurement
May 21, 2024
Myocarditis poses a significant health risk, often precipitated by viral infections like coronavirus disease, and can lead to fatal cardiac complications. As a less invasive alternative to the standard diagnostic practice of endomyocardial biopsy, wh...
Analysis of the improvement effect of Astragalus extract on oxidative stress injury in viral myocarditis through STAT3/IL-6.
Cellular and molecular biology (Noisy-le-Grand, France)
Dec 31, 2023
The objective of this study was to investigate the improvement effect of Astragalus (AS) extract on oxidative stress (OS) and inflammatory response of myocarditis (MYO) cells through the STAT3/IL-6 axis. For this purpose, The MYO model cells prepared...
Deep Learning-Based Medical Data Association Rules to Explore the Connectivity and Regulation Mechanism of miRNA-mRNA Network in Myocarditis.
Computational and mathematical methods in medicine
Sep 23, 2022
Acute, chronic myocarditis as myocardial localized or diffuse inflammation lesions is usually involving cardiac function in patients with severe adverse outcomes such as heart failure, sudden death, and no unified, but its pathogenesis clinical is ma...
Deep Learning Algorithm to Detect Cardiac Sarcoidosis From Echocardiographic Movies.
Circulation journal : official journal of the Japanese Circulation Society
Jun 26, 2021
BACKGROUND: Because the early diagnosis of subclinical cardiac sarcoidosis (CS) remains difficult, we developed a deep learning algorithm to distinguish CS patients from healthy subjects using echocardiographic movies.
Identification of prognostic factors for pediatric myocarditis with a random forests algorithm-assisted approach.
Pediatric research
Nov 18, 2020
BACKGROUND: Pediatric myocarditis is a rare disease with substantial mortality. Little is known regarding its prognostic factors. We hypothesize that certain comorbidities and procedural needs may increase risks of poor outcomes. This study aims to i...
An autopsy case of cardiac tamponade caused by a ruptured ventricular aneurysm associated with acute myocarditis.
Legal medicine (Tokyo, Japan)
Dec 8, 2015
We report an autopsy case of hemopericardium caused by rupture of a ventricular aneurysm associated with acute myocarditis in an infant boy aged 2 years and 10 months. Three days before his death, the patient developed fever. On the day of death, he ...
Using machine learning models based on cardiac magnetic resonance parameters to predict the prognostic in children with myocarditis.
BMC pediatrics
May 24, 2025
OBJECTIVE: To develop machine learning (ML) models incorporating explanatory cardiac magnetic resonance (CMR) parameters for predicting the prognosis of myocarditis in pediatric patients.
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