AIMC Topic: Cardiomyopathies

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A deep learning approach to identify and segment alpha-smooth muscle actin stress fiber positive cells.

Scientific reports Nov 8, 2021
Cardiac fibrosis is a pathological process characterized by excessive tissue deposition, matrix remodeling, and tissue stiffening, which eventually leads to organ failure. On a cellular level, the development of fibrosis is associated with the activa...
Image Processing, Computer-Assisted Fibroblasts Myofibroblasts Myocardium Cell Culture Techniques Humans Cardiomyopathies Artificial Intelligence Models, Cardiovascular Cells, Cultured Hydrogels Stress Fibers Deep Learning Actins Surface Properties Elasticity
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Feasibility of late gadolinium enhancement (LGE) in ischemic cardiomyopathy using 2D-multisegment LGE combined with artificial intelligence reconstruction deep learning noise reduction algorithm.

International journal of cardiology Sep 10, 2021
BACKGROUND: Despite the low spatial resolution of 2D-multisegment late gadolinium enhancement (2D-MSLGE) sequences, it may be useful in uncooperative patients instead of standard 2D single segmented inversion recovery gradient echo late gadolinium en...
Artificial Intelligence Algorithms Deep Learning Contrast Media Magnetic Resonance Imaging Feasibility Studies Gadolinium Cardiomyopathies Humans
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Phenogrouping Diastolic Dysfunction by Artificial Intelligence: Learning From What We Teach the Machines.

JACC. Cardiovascular imaging Jul 14, 2021
Algorithms Predictive Value of Tests Cardiomyopathies Humans Artificial Intelligence Machine Learning
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Artificial Intelligence-Enhanced Electrocardiogram for the Early Detection of Cardiac Amyloidosis.

Mayo Clinic proceedings Jul 2, 2021
OBJECTIVE: To develop an artificial intelligence (AI)-based tool to detect cardiac amyloidosis (CA) from a standard 12-lead electrocardiogram (ECG).
Humans Male Middle Aged United States Electrocardiography Neural Networks, Computer Artificial Intelligence Retrospective Studies Female Predictive Value of Tests Time-to-Treatment Area Under Curve Cardiomyopathies Early Diagnosis Amyloid Neuropathies, Familial
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Deep learning-based framework for cardiac function assessment in embryonic zebrafish from heart beating videos.

Computers in biology and medicine Jun 11, 2021
Zebrafish is a powerful and widely-used model system for a host of biological investigations, including cardiovascular studies and genetic screening. Zebrafish are readily assessable during developmental stages; however, the current methods for quant...
Myocardial Contraction Animals Deep Learning Zebrafish Cardiovascular System Cardiomyopathies
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A machine learning model for identifying patients at risk for wild-type transthyretin amyloid cardiomyopathy.

Nature communications May 11, 2021
Transthyretin amyloid cardiomyopathy, an often unrecognized cause of heart failure, is now treatable with a transthyretin stabilizer. It is therefore important to identify at-risk patients who can undergo targeted testing for earlier diagnosis and tr...
Prealbumin Cardiomyopathies Amyloid Neuropathies, Familial Humans Machine Learning Electronic Health Records Heart Failure
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Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach.

Scientific reports Apr 14, 2021
Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healt...
Veterans Risk Cardiomyopathies Aged Aged, 80 and over Male Middle Aged Comorbidity Renal Insufficiency, Chronic Myocardial Infarction International Classification of Diseases Humans Neural Networks, Computer Databases, Factual Female
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Prediction of Incident Heart Failure in TTR Val122Ile Carriers One Year Ahead of Diagnosis in a Multiethnic Biobank.

The American journal of cardiology Dec 18, 2020
Cardiomyopathies Penetrance Amyloid Neuropathies, Familial Clinical Decision Rules Heart Failure Biological Specimen Banks Black or African American Prealbumin Area Under Curve Mutation Hispanic or Latino Electronic Health Records Case-Control Studies Incidence ROC Curve Humans Machine Learning
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Using Artificial Intelligence to Detect, Classify, and Objectively Score Severity of Rodent Cardiomyopathy.

Toxicologic pathology Dec 8, 2020
Rodent progressive cardiomyopathy (PCM) encompasses a constellation of microscopic findings commonly seen as a spontaneous background change in rat and mouse hearts. Primary histologic features of PCM include varying degrees of cardiomyocyte degenera...
Neural Networks, Computer Artificial Intelligence Algorithms Animals Mice Rats Cardiomyopathies Rodentia
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Machine Learned Cellular Phenotypes in Cardiomyopathy Predict Sudden Death.

Circulation research Nov 10, 2020
RATIONALE: Susceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside.
Myocardial Infarction Aged Tachycardia, Ventricular Aged, 80 and over Prospective Studies Cardiomyopathies Male Ventricular Fibrillation Prognosis Death, Sudden, Cardiac Middle Aged Female Action Potentials Electrophysiologic Techniques, Cardiac Risk Factors Predictive Value of Tests Risk Assessment Humans Signal Processing, Computer-Assisted Diagnosis, Computer-Assisted Neural Networks, Computer Time Factors Phenotype Support Vector Machine
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