features | AI in Healthcare

Oasis of Opportunity: Strategies for Managing Healthcare’s Data Deluge

Forward-looking providers are converting reams of data from myriad sources into innovative new ways to deliver healthcare and improve efficiencies.

Bring on the Bots: Introducing AI into the Revenue Cycle

As costs continue to rise, healthcare organizations must become more efficient with collecting, says Anthony Cunningham, MBA, vice president of Patient Financial Services at Wake Forest Baptist Health. One approach, he explains, is deploying staff away from repetitive tasks and “toward high-value-add work.” That’s where artificial intelligence comes in.

How Secure Is That Scanner?

In a world of networked medical devices, it’s not hard to imagine a radiology-heavy cyberattack that is not only malicious but also ingenious.

Building Foundations to Build Better Care

It’s all about the data. We’ve been saying this for years. We can choose to look at this in one of two ways. It’s either a constant truism or it actually evolves and gains mass over time. In the age of artificial intelligence, it is both.

Machine Learning 101: Simplifying It One Term at a Time

Machine learning is one of the hottest topics in radiology and all of healthcare, but reading the latest and greatest ML research can be difficult, even for experienced medical professionals. A new analysis written by a team at Northern Ireland’s Belfast City Hospital and published in the American Journal of Roentgenology was written with that very problem in mind.

Intelligence & Insight: The Latest News in AI and Machine Learning

A compilation of the latest news in AI and machine learning

Leveraging Technology, Data and Patient Care: How Geisinger Is Interjecting Insight & Action

As an integrated health-delivery network comprising 13 hospital campuses, two research centers and a health plan with more than half a million subscribers sitting atop the biggest biobank with whole exome (DNA) sequence data in existence, Pennsylvania’s Geisinger Health System is one of the best-positioned institutions in the U.S. to explore the possibilities and initial successes of AI in healthcare. The institution is bringing complex algorithmic concepts to everyday patient care and showing others the path forward.

Embracing AI: Why Now Is the Time for Medical Imaging

Artificial and augmented intelligence are driving the future of medical imaging. Tectonic is the only way to describe the trend. And medical imaging is at the right place at the right time. Imaging stands to get better, stronger, faster and more efficient thanks to artificial intelligence, including machine learning, deep learning, convolutional neural networks and natural language processing. So why is medical imaging ripe for AI? Check out the opportunities and hear what experts have to say—and see what you should be doing now if you haven’t already started.

Around the web

Cardiovascular Business

AI predicts cardiovascular risk during CT scans—no invasive tests or contrast required

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.

Radiology Business

Use of AI in radiology revenue cycle management

Dave Walker, senior director of revenue cycle, Radiology Associates of North Texas, explains how his practice uses artificial intelligence for revenue cycle management during the Radiology Business Management Association (RBMA) 2024 meeting.

Cardiovascular Business

First-in-human trial shows potential of guiding CABG with cardiac CT and AI—no ICA required

An independent heart team blinded to ICA results was able to deliver helpful guidance for CABG procedures for 99.1% of patients using just CCTA and FFR_CT alone. This approach is safe and feasible, researchers wrote, and the next step is to gather additional data.