Predicting Lethal Outcome (Cause) And Understanding Key Biomarkers Linked With Acute Myocardial Infarction Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies
arXiv:2607.00472v1 Announce Type: cross Abstract: Cardiovascular disease is still one of the main causes of death around the world. Acute myocardial infarction (MI), or heart attack, claims millions of lives each year. MI happens when blood flow to the coronary arteries is blocked or reduced, which causes permanent damage to the heart muscle. Without treatment, this can lead to cardiac arrest, where the heart stops pumping blood to the organs, resulting in organ failure and death. Even survivors often face serious problems like heart failure, pulmonary edema, and asystole. Research shows that
Advances in deep learning and machine learning are enabling more sophisticated analysis of complex biological data, making AI applications in medical diagnostics increasingly viable.
This research highlights the growing capability of AI to provide predictive insights into critical health conditions, potentially revolutionizing early diagnosis and personalized treatment strategies for cardiovascular disease.
The ability to predict lethal outcomes and identify key biomarkers using AI could transform how acute myocardial infarction is detected and managed, moving towards more proactive intervention.
- · Healthcare providers
- · Patients at risk of cardiovascular disease
- · AI in medicine sector
- · Biomedical research
Improved early diagnosis and risk stratification for acute myocardial infarction patients.
Development of more targeted therapies and preventative measures based on AI-identified biomarkers.
Reduced healthcare costs associated with critical cardiovascular events due to earlier intervention and better patient management.
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