New machine learning model predicts cardiac arrest in ICU patients using ECG data with high accuracy
In a recent article published in Npj Digital Medicine, researchers utilized electrocardiogram (ECG) data from a large retrospective cohort to extract various heart rate variability (HRV) measures.
The mortality risk for individual cardiac surgery patients can be predicted with a machine learning-based model developed by researchers at Mount Sinai Hospital in New York. The new data-driven ...
Drosophila - commonly known as fruit flies - are a valuable model for human heart pathophysiology, including cardiac aging and cardiomyopathy. However, a choke point in evaluating fruit fly hearts is ...
The global AI in cardiology market size is expected to reach USD 14.83 billion by 2033, registering a CAGR of 31.17% from ...
Girish Melkani and Team Leverage Machine Learning to Uncover Insights into Cardiac Aging and Disease
Melkani's study, “Automated assessment of cardiac dynamics in aging and dilated cardiomyopathy Drosophila models using machine learning,” was published in Communications Biology (A Nature Portfolio ...
Please provide your email address to receive an email when new articles are posted on . Familial hypercholesterolemia is underdiagnosed and undertreated. A novel machine learning algorithm identified ...
At the Cardiology Summa2024 in Delhi, experts highlighted AI's transformative impact on cardiac care. Dr. Balbir Singh and Dr. Gurpreet Sandhu emphasized AI's role in early heart disease detection, ...
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