Medical technology: CPR training kiosk opens, researchers study AI in medicine

CHARLESTON, S.C. (WCSC) - Two initiatives are underway across the Lowcountry aimed at leveraging health outcomes.

Starting Tuesday, North Charleston Coliseum attendees will be able to learn hands-only CPR at an automated kiosk.

The new trainer, the first in the area, is a partnership between the American Heart Association and software company Blackbaud. The touchscreen device has a manikin attached to it. After a short training, a 30-second test is administered. The kiosk gives the participant feedback about hand placement, as well as depth and rate of compressions.

The American Heart Association says about 16% of cardiac arrests occur in a public setting, and hands-only CPR can double or triple the chance of survival when it is performed immediately. The goal is to train as many individuals as possible, including through kiosks like this.

“Why not take the few minutes? Blackbaud Chief People and Culture Officer Maggie Driscoll said. “Think about that impact. You really may be in a position to save a family member, a colleague or any individual.”

About 16% of cardiac arrests occur in a public setting. And CPR can double or triple the chance of survival when it is performed immediately.

MUSC Researchers Studying AI in Medicine

The breakthroughs behind “ChatGPT”, the artificial intelligence chatbot from OpenAI, dominated the headlines over the past few months.

AI technology is not new, but medical researchers said there have been similar breakthroughs in machine learning technologies that they are studying. The Medical University of South Carolina has an “AI Hub” in collaboration with Clemson University.

MUSC Assistant Professor of Medicine Dr. Ramsey Wehbe studies artificial intelligence.

“This technology is not meant to replace your doctor, not meant to replace your care team,” he said. It’s simply meant to give them tools to help take care of you in a better way.”

Researchers see it as a possible way to offload some of the more mundane tasks for clinicians to prevent your doctor from being able to spend more time with you the patient.

Though the technology has grown exponentially, there are a few barriers to work through. First, the infrastructure to test algorithms in a clinical setting is limited. MUSC researchers need to build out the infrastructure for tests.

Additionally, Wehbe said, concerns about pattern-recognition algorithms not performing well on new data is something researchers are working through. Like any new technology, it requires scientific due diligence before it is brought to the patient’s bedside.

“In 10 years, we’re going to be looking back at this as not ‘AI in medicine,’” Wehbe said. “It’s just going to be ‘medicine.’”

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