Promising heart drugs ID'd by cutting-edge combo of machine learning, human learning. ScienceDaily . Retrieved May 27, 2025 from www.sciencedaily.com / releases / 2024 / 02 / 240201121723.htm ...

UC San Francisco researchers have found a way to double doctors’ accuracy in detecting the vast majority of complex fetal heart defects in utero – when interventions could either correct them or ...

As compared to traditional methods, machine learning models can use a vast number of input features, enabling them to improve and enhance the identification of individuals at risk.

Researchers at the University of Alabama at Birmingham now show a way to significantly cut the time needed for that analysis while utilizing more of the heart region, using deep learning and ...

The machine learning algorithm was "taught" using the patient’s sex, age, ECG findings and medical history, in addition to troponin levels, to identify the probability that a heart attack had ...

Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction Go to source ). The study utilized data from 7,313 consecutive patients with chest pain across ...

Using machine learning, the researchers determined that of the tested metrics, EKGs were most effective at improving the detection of cardiovascular disease in both men and women. This, however, does ...

New research uses machine learning to mine data from standard lung-cancer scans and predict patients most likely to have heart damage from radiation treatment later in life.