“Today marks an important milestone in GE’s history,” CEO John Flannery said at the time. “We are aggressively driving forward as an aviation, power and renewable energy company – three highly complementary businesses poised for future growth. We will continue to improve our operations and balance sheet as we make GE simpler and stronger.”

In December, insiders told Bloomberg News that GE filed confidentially for a healthcare IPO.

A public filing is likely next spring, the sources said.

RSNA and the year of AI (part 2)

Anyone who still says 2017 was the year of AI at RSNA probably wasn't at RSNA 2018. Smart algorithms and deep learning continued to take over the industry with a vast range of applications and tools in various stages of development.

Skeptics would be correct to pause and point out that the actual real-world benefit of these systems is still being determined, but the industry seems committed to the idea that AI is a game-changer and radiology will never be the same.

At RSNA, a panel of three physician experts in developing AI imaging platforms and one manufacturing CEO shared their insight in a lively discussion entitled "Medical Imaging Analytics & AI: Technologies and Solutions for Better Healthcare Today and in the Future,".

Patients and radiologists alike want to reduce dose and gadolinium exposure. According to Dr. Greg Zaharchuk, professor of Radiology at Stanford University and founder of Subtle Medical, AI can do that. He added that those are the first places where successful AI solutions will emerge.

Gene Saragnese, CEO MaxQ and past CEO of Philips Imaging, said that apps that work on both low-end and high-end systems will be the most desirable and therefore the first to penetrate the market.

A killer AI app would be one that counts lung nodules under low-dose CT, said Dr. Eliot Siegel, chief of Radiation Oncology for the VA Maryland Healthcare System, citing the process as "tedious" and requiring a lot of work to submit the report to a registry for reimbursement. Ushering AI into that element of workflow would reduce cost and make the procedure more widely available, he said.

Machines can see a tumor earlier, with more accuracy than humans – we know that, said Dr. Lei Xing, professor and director of Medical Physics at Stanford. However, he added, the best AI app will take that info and combine it with other patient data from other clinical sources to fundamentally change value. It might predict, for example, which patients will respond to certain treatments based, in part, on genomic information coupled with the image analysis.

More Industry Headlines