Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
FIU Researchers are training AI to detect heart conditions, like aortic stenosis and heart failure, by analyzing heart sound data to improve early diagnosis and risk prediction. The future of heart ...
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Physical function metrics improve mortality prediction in elderly heart failure patients
Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may ...
COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...
A research team from Juntendo University in Japan wanted to find a better way to predict survival for older people with heart failure. The project was led by Professor Tetsuya Takahashi, Assistant ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Adults with congenital heart disease (CHD) have a persistently high risk for cardiac reoperation, according to a new study.
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