-
Using electrocardiogram data, Geisinger researchers have trained deep neural networks to predict patients’ risk of developing a potentially dangerous irregular heartbeat or of dying within the next 12 months.November 11
-
Atrius Health, New England’s largest independent medical group, has partnered with Alphabet’s life sciences division Verily to better treat heart failure patients and reduce their risk of hospitalization.October 28
-
Using large healthcare encounter datasets, a machine learning algorithm is able to identify patients with a common genetic disorder that carries a high risk for early heart attacks and strokes.October 22
-
James Park, co-founder and CEO of Fitbit, contends that while wearable fitness trackers started as “nice to have” consumer devices, they are fast becoming “must have” technology for managing health.October 18
-
Vanderbilt University Medical Center researchers have identified 14 distinct cardiovascular disease patient subtypes using unsupervised machine learning on unlabeled electronic health record data.October 10
-
An approach for bringing artificial intelligence to computed tomography studies to help radiologists better interpret chest images has received federal clearance for use.September 27
-
Engineers, researchers and physician scientists are leveraging imaging and image processing technologies to improve outcomes.September 23
-
Danville, Penn.-based Geisinger is teaming with tech vendor Tempus to leverage artificial intelligence for the development of diagnostic and prognostic tools for cardiovascular disease.September 18
-
Researchers have identified the 10 top predictors of future heart failure for patients living with type 2 diabetes by using a machine learning model that generates a risk score.September 16
-
Remote blood pressure monitoring is an effective tool for managing hypertension in postpartum women at home after hospital discharge.September 12
