AIMC Topic: Myocardium

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Investigating methods to enhance interpretability and performance in cardiac MRI for myocardial scarring diagnosis using convolutional neural network classification and One Match.

PloS one
Machine learning (ML) classification of myocardial scarring in cardiac MRI is often hindered by limited explainability, particularly with convolutional neural networks (CNNs). To address this, we developed One Match (OM), an algorithm that builds on ...

One-Drop Serum Screening Test to Monitor Tissue Iron Accumulation.

Analytical chemistry
Although iron is an essential element for vital body functions, iron overload (IO) is accompanied by significant cellular damage due to its accumulation within organs. Thus, early diagnosis and accurate identification of the affected organs are criti...

Gui-Pi-Tang Defers Skeletal Muscle and Cardiac Muscle Aging by Promoting Mitochondrial Remodeling.

Drug design, development and therapy
PURPOSE: To determine whether Gui-Pi-Tang (GPT) has protective effects on skeletal muscle and cardiac muscle in aged mice.

U-shaped network combining dual-stream fusion mamba and redesigned multilayer perceptron for myocardial pathology segmentation.

Medical physics
BACKGROUND: Cardiac magnetic resonance imaging (CMR) provides critical pathological information, such as scars and edema, which are vital for diagnosing myocardial infarction (MI). However, due to the limited pathological information in single-sequen...

Proteomics and Machine Learning-Based Approach to Decipher Subcellular Proteome of Mouse Heart.

Molecular & cellular proteomics : MCP
Protein compartmentalization to distinctive subcellular niches is critical for cardiac function and homeostasis. Here, we employed a rapid and robust workflow based on differential centrifugal-based fractionation with mass spectrometry-based proteomi...

Deep Learning-Enhanced Chemiluminescence Vertical Flow Assay for High-Sensitivity Cardiac Troponin I Testing.

Small (Weinheim an der Bergstrasse, Germany)
Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grade sensitivity and precision in an accessible format. Here, high-sensitivity detection of cardiac troponin I (cTnI) is demonstrated through innovations...

Machine learning-based interpretation of non-contrast feature tracking strain analysis and T1/T2 mapping for assessing myocardial viability.

Scientific reports
Assessing myocardial viability is crucial for managing ischemic heart disease. While late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is the gold standard for viability evaluation, it has limitations, including contraindicati...

A novel deep learning based method for myocardial strain quantification.

Biomedical physics & engineering express
This paper introduces a deep learning method for myocardial strain analysis while also evaluating the efficacy of the method across a public and a private dataset for cardiac pathology discrimination.We measure the global and regional myocardial stra...

Deep learning automatically distinguishes myocarditis patients from normal subjects based on MRI.

The international journal of cardiovascular imaging
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...