AI for diabetic retinopathy

Buzzworthy developments of the past few days.

physician artificial intelligence

AI adoption for real-world healthcare settings can’t happen in a vacuum. 

artificial intelligence in healthcare

Buzzworthy developments of the past few days.

artificial intelligence for family medicine primary care

ChatGPT is only so-so at letting physicians know if any given clinical study is relevant to their patient rosters and, as such, deserving of a full, time-consuming read. On the other hand ... 

artificial intelligence AI in healthcare

Buzzworthy developments of the past few days.

artificial intelligence kaiser permanente

Imperfect algorithms. Resistant clinicians. Wary patients. Divisive disparities. The plot ingredients of a flashy techno-thriller coming to a cineplex near you? No—just a few of the many worries that provider organizations take on when they move to adopt AI at scale. 

artificial intelligence code face

Buzzworthy developments of the past few days.

artificial intelligence gold rush

It’s more critical for U.S. healthcare to get medical AI right than to get it adopted far, wide and ASAP.

By using the CRISPR gene-editing tool, a research team was able to identify several mutations in cells that boosted the risk of cancer.

Tablet projecting metaphorical medical hologram

A majority of physicians weren’t asked by electronic health record (EHR) vendors to provide feedback while making enhancements to EHR systems, according to the Deloitte 2018 Survey of U.S. Physicians.

University of British Columbia engineers have created a new ultrasound machine that’s reportedly “no bigger than a Band-Aid” and could lower the cost of ultrasound scanners to $100.

Several hospitals and healthcare organizations are now taking advantage of electronic data-sharing systems that provide real-time alerts about what’s happening within a facility, according to a report by Politico.

Around the web

A new scientific statement from the American Heart Association explores the many ways AI and machine learning are being used to improve care for heart patients.

The new collaboration is designed to ensure patients who may face an increased risk of heart disease receive the follow-up care they need.

The new algorithm from Viz.ai is capable of identifying, labeling and quantifying brain bleeds in noncontrast CT images.