AIMC Topic: Myocardial Infarction

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Early diagnostic biomarkers for acute myocardial infarction unveiled by metabolomics, Mendelian randomization, and machine learning.

Molecular biomedicine
Acute myocardial infarction (AMI) remains a leading cause of global cardiovascular morbidity and mortality. Limitations in current diagnostic methods hinder early detection and intervention, creating an urgent need for novel early diagnostic biomarke...

Deciphering the clinical implication of an obesity-related gene signature as the novel biomarker for acute myocardial infarction diagnosis.

Scientific reports
Acute myocardial infarction (AMI) stands as a major contributor to mortality and disability worldwide, with obesity playing a significant role in its development. This study aims to investigate potential biomarkers associated with obesity-related gen...

AI-powered SPOT imaging for enhanced myocardial scar detection and quantification.

Nature communications
Cardiovascular disease is the leading global cause of death, underscoring the need for accurate assessment of myocardial injury. The current gold standard, bright-blood late gadolinium enhanced MRI, suffers from poor contrast at the blood-scar interf...

Prioritization of patients at risk of heart attack using a novel full-objective ITARA based on Random Forest and Decision tree.

Scientific reports
Heart attacks remain a major cause of morbidity and mortality, particularly among middle-aged and older adults, often aggravated by unhealthy lifestyles and limited preventive care. Early identification and prioritization of at-risk individuals are e...

Identification and validation of biomarkers associated with cellular senescence and demethylation in acute myocardial infarction.

Scientific reports
Acute myocardial infarction (AMI) triggered cardiomyocyte senescence and impaired cardiac function. Methylation modifications and related enzymes in patients were also significantly altered, but the association between cellular senescence and demethy...

Classification of cardiac electrical signals between patients with myocardial infarction and healthy controls by using time-frequency features and 3D convolutional neural networks.

Biomedical physics & engineering express
Electrocardiogram (ECG) signal classification plays an important role in myocardial infarction (MI) detection and screening. Despite that much progress has been made, the interpretation of ECG signals is still extremely time-consuming, and heavily re...

Optimizing myocardial infarction detection: a hybrid CNN-GRU deep learning approach.

BMC medical informatics and decision making
BACKGROUND: Myocardial infarction (MI) is a life-threatening condition caused by sudden interruption of blood supply to the heart. Electrocardiogram (ECG) is the primary tool for MI diagnosis, but interpretation challenges exist. This study aimed to ...

Human-Delivered Conversation Versus AI Chatbot Conversation in Increasing Heart Attack Knowledge in Women in the United States: Quasi-Experimental Studies.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) chatbots, driven by advances in natural language processing, can analyze and generate human language through computational linguistics and machine learning. Despite the rapid development of large language mode...

AI HeartBot to Increase Women's Awareness and Knowledge of Heart Attacks: Nonrandomized, Quasi-Experimental Study.

JMIR cardio
BACKGROUND: Heart disease remains a leading cause of death for women in the United States, but awareness and knowledge about it are declining. Artificial intelligence (AI) chatbots have great potential to educate women.