Brown, K., et al. (2024) Using Artificial Intelligence for Rheumatic Heart Disease Detection by Echocardiography: Focus on Mitral Regurgitation. Journal of the American Heart Association. doi.org ...

In recent years, by using tremendous amounts of EHR data, researchers have trained deep learning models to extract disease progression insights, but this predictive modelling has primarily focused ...

When Kelsey Brown met Mohammed, the 15-year-old Ugandan boy looked terribly worried. He was in the late stages of rheumatic heart disease, which kills about 400,000 people a year worldwide.

The developers of Cardiogram, a consumer heart rate-tracking app, have launched a study aiming to use deep learning to detect atrial fibrillation. Skip to Main Content Explore Our Brands ...

To evaluate the diagnostic performance of their deep-learning model, the researchers calculated the area under the receiver operating characteristic curve (AUC) for nine primary classifiers – a cutoff ...

(HealthDay)—Handheld echocardiography (HAND) and auscultation improves detection of rheumatic heart disease (RHD) compared with auscultation alone, according to a study published online March 16 ...

Karki, P., et al. (2021) Effectiveness of Systematic Echocardiographic Screening for Rheumatic Heart Disease in Nepalese Schoolchildren A Cluster Randomized Clinical Trial. JAMA Cardiology. doi ...

Melkani envisions using deep learning-assisted studies to explore cardiac mutation models and other small animal models, such as zebrafish and mice. “Additionally, our techniques could be adapted for ...

Deep machine-learning speeds assessment of fruit fly heart aging and disease, a model for human disease. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2024 / 07 ...