AI Model Identifies Diabetic Patients at High Risk for Heart Failure
The AI tool detects a specific high-risk group of diabetic patients with abnormal heart function, which raises their risk of heart failure.
Category: Predictive Analytics
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Heat-Related Cardiovascular Deaths Predicted to Rise
Cardiovascular-related deaths due to extreme heat are expected to increase between 2036 and 2065 in the United States, according to a study supported by the National Institutes of Health.
Revolutionizing Cardiovascular Health: The Power of AI in Predicting Disease
Artificial intelligence (AI) is revolutionizing cardiovascular health prediction, offering the potential for more accurate risk assessments and personalized interventions. Through machine learning algorithms and analysis of medical imaging, AI empowers healthcare professionals to make informed decisions and save lives.
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HeartBEiT: The AI Breakthrough That Transforms ECG Analysis into Language
Mount Sinai researchers have developed HeartBEiT, an AI model that interprets electrocardiograms (ECGs) as language, revolutionizing ECG analysis. With superior performance and “explainability,” HeartBEiT enhances diagnostic accuracy for cardiac conditions and offers insights into heart health. Discover the transformative potential of this groundbreaking innovation in the field of medical technology.
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The Link Between Neonatal Depression and Mortality in Critical Congenital Heart Disease: Insights from National Data
A new study using US national vital statistics data sheds light on the link between neonatal depression (low Apgar scores) and 1-year mortality in critical congenital heart disease (CCHD). The study identifies risk factors for neonatal depression and highlights the importance of using Apgar scores as a prognostic indicator in CCHD. These findings have implications for prenatal management and improving CCHD mortality rates.
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