AIMC Topic: Echocardiography
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Development and validation of a machine learning-based approach to identify high-risk diabetic cardiomyopathy phenotype.
European journal of heart failure
Sep 6, 2024
AIMS: Abnormalities in specific echocardiographic parameters and cardiac biomarkers have been reported among individuals with diabetes. However, a comprehensive characterization of diabetic cardiomyopathy (DbCM), a subclinical stage of myocardial abn...
A multi-task deep learning approach for real-time view classification and quality assessment of echocardiographic images.
Scientific reports
Sep 3, 2024
High-quality standard views in two-dimensional echocardiography are essential for accurate cardiovascular disease diagnosis and treatment decisions. However, the quality of echocardiographic images is highly dependent on the practitioner's experience...
Artificial intelligence guided screening for cardiomyopathies in an obstetric population: a pragmatic randomized clinical trial.
Nature medicine
Sep 2, 2024
Nigeria has the highest reported incidence of peripartum cardiomyopathy worldwide. This open-label, pragmatic clinical trial randomized pregnant and postpartum women to usual care or artificial intelligence (AI)-guided screening to assess its impact ...
Automated echocardiographic diastolic function grading: A hybrid multi-task deep learning and machine learning approach.
International journal of cardiology
Aug 30, 2024
BACKGROUND: Assessing left ventricular diastolic function (LVDF) with echocardiography as per ASE guidelines is tedious and time-consuming. The study aims to develop a fully automatic approach of this procedure by a lightweight hybrid algorithm combi...
EFNet: A multitask deep learning network for simultaneous quantification of left ventricle structure and function.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Aug 28, 2024
PURPOSE: The purpose of this study is to develop an automated method using deep learning for the reliable and precise quantification of left ventricle structure and function from echocardiogram videos, eliminating the need to identify end-systolic an...
Definition and Validation of Prognostic Phenotypes in Moderate Aortic Stenosis.
JACC. Cardiovascular imaging
Aug 14, 2024
BACKGROUND: Adverse outcomes from moderate aortic stenosis (AS) may be caused by progression to severe AS or by the effects of comorbidities. In the absence of randomized trial evidence favoring aortic valve replacement (AVR) in patients with moderat...
Female
Reproducibility of Results
Risk Factors
Aged
Aged, 80 and over
Male
Aortic Valve
Echocardiography
Unsupervised Machine Learning
Middle Aged
Heart Failure
Severity of Illness Index
Humans
Predictive Value of Tests
Phenotype
Risk Assessment
Time Factors
Cluster Analysis
Prognosis
Comorbidity
Aortic Valve Stenosis
A Shape-Consistent Deep-Learning Segmentation Architecture for Low-Quality and High-Interference Myocardial Contrast Echocardiography.
Ultrasound in medicine & biology
Aug 14, 2024
OBJECTIVE: Myocardial contrast echocardiography (MCE) plays a crucial role in diagnosing ischemia, infarction, masses and other cardiac conditions. In the realm of MCE image analysis, accurate and consistent myocardial segmentation results are essent...
Applying masked autoencoder-based self-supervised learning for high-capability vision transformers of electrocardiographies.
PloS one
Aug 14, 2024
The generalization of deep neural network algorithms to a broader population is an important challenge in the medical field. We aimed to apply self-supervised learning using masked autoencoders (MAEs) to improve the performance of the 12-lead electro...
A Deep-Learning-Enabled Electrocardiogram and Chest X-Ray for Detecting Pulmonary Arterial Hypertension.
Journal of imaging informatics in medicine
Aug 13, 2024
The diagnosis and treatment of pulmonary hypertension have changed dramatically through the re-defined diagnostic criteria and advanced drug development in the past decade. The application of Artificial Intelligence for the detection of elevated pulm...
High-Throughput Deep Learning Detection of Mitral Regurgitation.
Circulation
Aug 12, 2024
BACKGROUND: Diagnosis of mitral regurgitation (MR) requires careful evaluation by echocardiography with Doppler imaging. This study presents the development and validation of a fully automated deep learning pipeline for identifying apical 4-chamber v...
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