AIMC Topic: Myocardial Infarction
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An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar.
Computer methods and programs in biomedicine
Dec 20, 2022
BACKGROUND AND OBJECTIVES: Myocardial infarction scar (MIS) assessment by cardiac magnetic resonance provides prognostic information and guides patients' clinical management. However, MIS segmentation is time-consuming and not performed routinely. Th...
Development and validation of deep learning ECG-based prediction of myocardial infarction in emergency department patients.
Scientific reports
Nov 15, 2022
Myocardial infarction diagnosis is a common challenge in the emergency department. In managed settings, deep learning-based models and especially convolutional deep models have shown promise in electrocardiogram (ECG) classification, but there is a l...
Direct Risk Assessment From Myocardial Perfusion Imaging Using Explainable Deep Learning.
JACC. Cardiovascular imaging
Oct 19, 2022
BACKGROUND: Myocardial perfusion imaging (MPI) is frequently used to provide risk stratification, but methods to improve the accuracy of these predictions are needed.
Artificial Intelligence for Contrast-Free MRI: Scar Assessment in Myocardial Infarction Using Deep Learning-Based Virtual Native Enhancement.
Circulation
Sep 20, 2022
BACKGROUND: Myocardial scars are assessed noninvasively using cardiovascular magnetic resonance late gadolinium enhancement (LGE) as an imaging gold standard. A contrast-free approach would provide many advantages, including a faster and cheaper scan...
Machine Learning Methods in Predicting Patients with Suspected Myocardial Infarction Based on Short-Time HRV Data.
Sensors (Basel, Switzerland)
Sep 17, 2022
Diagnosis of cardiovascular diseases is an urgent task because they are the main cause of death for 32% of the world's population. Particularly relevant are automated diagnostics using machine learning methods in the digitalization of healthcare and ...
Automated Detection of Myocardial Infarction and Heart Conduction Disorders Based on Feature Selection and a Deep Learning Model.
Sensors (Basel, Switzerland)
Aug 29, 2022
An electrocardiogram (ECG) is an essential piece of medical equipment that helps diagnose various heart-related conditions in patients. An automated diagnostic tool is required to detect significant episodes in long-term ECG records. It is a very cha...
From Classic to Modern Prognostic Biomarkers in Patients with Acute Myocardial Infarction.
International journal of molecular sciences
Aug 15, 2022
Despite all the important advances in its diagnosis and treatment, acute myocardial infarction (AMI) is still one of the most prominent causes of morbidity and mortality worldwide. Early identification of patients at high risk of poor outcomes throug...
Application of artificial intelligence techniques for automated detection of myocardial infarction: a review.
Physiological measurement
Aug 3, 2022
Myocardial infarction (MI) results in heart muscle injury due to receiving insufficient blood flow. MI is the most common cause of mortality in middle-aged and elderly individuals worldwide. To diagnose MI, clinicians need to interpret electrocardiog...
Artificial Intelligence and Cardiovascular Magnetic Resonance Imaging in Myocardial Infarction Patients.
Current problems in cardiology
Jul 21, 2022
Cardiovascular magnetic resonance (CMR) is an important cardiac imaging tool for assessing the prognostic extent of myocardial injury after myocardial infarction (MI). Within the context of clinical trials, CMR is also useful for assessing the effica...
Artificial intelligence fully automated myocardial strain quantification for risk stratification following acute myocardial infarction.
Scientific reports
Jul 18, 2022
Feasibility of automated volume-derived cardiac functional evaluation has successfully been demonstrated using cardiovascular magnetic resonance (CMR) imaging. Notwithstanding, strain assessment has proven incremental value for cardiovascular risk st...
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