Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

Novel AI algorithm beats cardiologists' models in predicting heart disease mortality

A machine learning model developed by scientists at the Francis Crick Institute in London can more accurately predict risk of death in patients with heart disease than leading models designed by medical experts, according to a study published in PLOS One.

September 4, 2018

FDA-approved AI echocardiogram software bests cardiologists in reducing LVEF variability

A deep-learning software that can automatically calculate left ventricular ejection fraction (LVEF) with less variability than a cardiologist recently received approval from the U.S. Food and Drug Administration (FDA).

June 26, 2018

Combination of wearables, AI may help ID onset of cardiovascular disease

Wearable sensors and artificial intelligence (AI) could help predict the onset of cardiovascular disease by assessing an individual's changes in aerobic responses, according to new research published on Feb. 23 in the Journal of Applied Physiology.

May 17, 2018

FDA clears AI platform that quickly alerts specialists to strokes

The FDA cleared Viz.ai’s clinical support tool on Feb. 13, allowing the software that alerts clinicians to the possibility of a stroke to be marketed in the United States.

February 15, 2018

Health AI Startup Medial EarlySign Predicts Which Diabetic Patients Will Suffer Kidney Damage Within One Year

KFAR MALAL, Israel, Feb. 5, 2018 — Medial EarlySign, a leader of machine-learning based solutions to improve non-communicable disease management, today announced the results of an additional clinical data study in the domain of diabetes — identifying diabetic patients who are at highest risk for having renal dysfunction within one year.

February 6, 2018

Mount Sinai to utilize AI for cardiovascular care

To better use technology to treat congestive heart failure, New York’s Mount Sinai Hospital has plans to use CloudMedx Clinical AI Platform, an artificial intelligence services software, reports Fortune.

October 18, 2016

High marks for telestroke evaluation

Medical images viewed on smartphones can be effectively used to remotely evaluate stroke patients through telemedicine, according to a study published online ahead of print in Stroke.

October 3, 2012

Around the web

Eleven medical societies have signed on to a consensus statement aimed at standardizing imaging for suspected cardiovascular infections.

Kate Hanneman, MD, explains why many vendors and hospitals want to lower radiology's impact on the environment. "Taking steps to reduce the carbon footprint in healthcare isn’t just an opportunity," she said. "It’s also a responsibility."

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