Generative AI in healthcare: transforming medical innovation

The integration of generative AI in healthcare is pushing the boundaries of medical innovation.

With advanced computing power and strategic collaborations, healthcare providers are beginning to harness these technologies to achieve unprecedented efficiency and improved patient outcomes. One such example is the application of multimodal generative AI models in radiology, which has demonstrated significant improvements in performance and quality of care, according to Kris Kristinsdóttir (pictured), machine learning engineer associate at Northwestern Medicine.

Northwest Medicine’s Kris Kristinsdóttir talks to theCUBE about generative AI in healthcare.

“One of our more exciting projects right now is a multimodal generative AI model that can look at an X-ray image and generate a report. We have this model live in our hospital system,” Kristinsdóttir said. “We have 50 radiologists using it since this summer, and we’re seeing some incredible performance improvements. The radiologists are 40% more efficient and they’re giving us feedback like, ‘Now, we get to spend more time doing what we actually love to do.’”

Kristinsdóttir spoke with theCUBE Research’s John Furrier and Savannah Peterson at Dell Technologies World, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the integration of generative AI in radiology for improved efficiency and accuracy, the technical advancements and the infrastructure supporting AI projects at Northwestern Medicine. (* Disclosure below.)

Advancements in generative AI in healthcare efficiency

Looking ahead, Northwestern Medicine aims to expand the capabilities and reach of its AI innovations. The ultimate goal is to roll out these advancements to other hospitals and radiologists worldwide, potentially revolutionizing the standard of care in medical imaging, Kristinsdóttir explained.

“We want to be able to help as many people as we can. But another vision we have, and another thing we would like to see is that every hospital has their own AI team and their own AI factory,” she said. “I mean, the healthcare and life sciences industry is responsible for generating more than 30% of all data generated globally. Within our hospitals, we’re only using 3% of that data. There’s so much data that we’re not leveraging that we can use to help us solve problems.”

Northwestern Medicine is also exploring the development of a comprehensive digital twin for its hospital system. This model would integrate various data sources, from sensor readings to lab tests, to simulate and predict patient outcomes, ultimately enabling more personalized and effective care strategies, Kristinsdóttir said.

“What if we can actually create some sort of digital twin for the system that will enable us to say, ‘Okay, if this part looks like this and we put it in this environment, what’s the outcome going to be, what is the future of this patient? Can we predict future disease states? Can we predict response to treatment and provide a more personalized care? For example, suggest an optimized diet,’” she said. “That’s something we’re very interested in.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of Dell Technologies World:

(* Disclosure: Dell Technologies Inc. sponsored this segment of theCUBE. Neither Dell Technologies nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE