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. 

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AI not 'economically viable' if it doesn't replace at least some radiologists, experts claim

“Ignoring the economic drivers of automation will not prevent workforce transformation; it will only reduce our ability to shape it."

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Users on a Discord chat are playing with Mythos, an AI deemed too dangerous for the public

Developer Anthropic released the tool to a small number of organizations in hopes they can find security vulnerabilities. Now comes a report revealing that a group of people on the popular Discord chat app have gained access. Mythos could be used as a powerful cybersecurity weapon.

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New study offers insight into the type of AI radiologists prefer

Members of the specialty are more likely to trust domain-specific models when it comes to report generation support, research suggests. 

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An ‘AI-native’—and lavishly funded—medical center grows in Texas

The largest single component of the overall project is likely to be the high-tech, high-touch hospital that’s now slated for opening in 2030.

GE HealthCare touts international expansion of its partnership with RadNet

The companies say they’re entering the next phase of collaboration, offering GEHC mammography systems paired with AI offerings from DeepHealth. 

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Healthcare AI often arrives with great expectations only to disappoint end-users as well as execs. Why is that?

By and large, U.S. hospitals and health systems do not have an AI adoption problem. But many—if not most—have an execution problem: They struggle to turn a set of installed AI tools into a measurable operational value. 

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Interventional radiologist launches AI-powered, IR-specific decision support platform

Developed by a board-certified diagnostic and interventional radiologist, the platform was trained using subspecialty data that general AI applications typically lack.

AI in healthcare

AI scribes add at least $167 per month to clinician income: 5-site study

In the three or so years since it burst into healthcare, ambient AI scribe technology has run away with the win in the market-uptake race. What has been the return on investment in all those software packages?