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. 

GE HealthCare

RadNet stock surges 20% to all-time high following news of GE HealthCare partnership

Under the “strategic collaboration,” subsidiary DeepHealth and GE will develop solutions that harness AI to address key challenges in radiology. 

artificial intelligence AI value

6 things high-achieving orgs do to wring real value from AI

What makes an organization an AI leader? Demonstrating success in one of two pursuits. 

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New AI-based software uses ultrasound images to guide clinical decisions during childbirth

Experts believe the tool has “excellent” potential to help guide decisions during labor and delivery in the future.

Predicting sudden cardiac death after a heart attack may be impossible—for now

Researchers tried to crack the code, but they fell short time and time again. AI may offer potential as one way to finally find an answer, they added. 

artificial intelligence technology

Industry Watcher’s Digest

The VA is throwing in with the FDA to launch a cross-agency AI testing facility. 

AI regulation

A modest proposal to rally AI regulators around a simple game plan

As debate simmers over how best to regulate AI, experts continue to offer guidance on where to start, how to proceed and what to emphasize. A new resource models its recommendations on what its authors call the “SETO Loop.”

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Deep learning reconstruction cuts prostate MRI acquisition time

And the shorter scan time does not come at the expense of image quality.

AI model spots missed breast cancers on MRI

AI model spots up to 30% of breast cancers missed on MRI

Re-evaluation by the second look algorithm could result in a cancer diagnosis up to one year earlier, especially for high risk disease.