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.

NYU’s Daniel Sodickson on AI, Facebook and Why Faster MR Scans Could Improve Healthcare

A new project is seeking to make MRI scans up to 10 times faster by capturing less data. NYU’s Center for Advanced Imaging Innovation and Research (CAI2R) is working with the Facebook Artificial Intelligence Research group to “train artificial neural networks to recognize the underlying structure of the images to fill in views omitted from the accelerated scan.”

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.

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Healthcare AI Startups See Record Deals

AI is hotter than hot in healthcare, according to AI market watcher CB Insights. Healthcare-AI funding reached $2.14 billion across 323 deals from 2012 through the second quarter of 2017—and has consistently been the top industry for AI deals.

Who Is JASON and Why Does He Care About Healthcare?

(Spoiler alert: It’s a 69-page report that indicates the use of AI in healthcare is both promising and doable.)

Pipeline Aplenty: FDA Greenlighting Medical AI Apps

When it comes to AI and machine learning, the regulatory trail has been blazed and the approval gates through open. The FDA has approved a couple dozen apps over the last year and a half—and the momentum is clearly building with Scott Gottlieb at the agency’s helm and recent moves to ramp up staffing to meet the demand.

An Inside-out Look at AI in Outpatient Radiology

Lawrence Tanenbaum is a big believer in AI, as a tool to create better images, offer a more comprehensive view of a patient and more effectively handle imaging’s increasing volume and complexity. Bigger yet, AI is the impetus to change the way radiology and medicine are practiced across the care spectrum.

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.