Better images expected to lead AI outcomes for 2019

According to one stakeholder, AI’s ability to process and interpret vast amounts of data will spread across healthcare as a major advantage in 2019 and beyond.
Jeff Rowe

If you think the internet had an impact on healthcare, wait and see what artificial intelligence will do.

That’s one way to sum up a recent commentary by John Stevens, CEO HostingFacts, a web services provider, in which he points to a number of problems across the healthcare sector that AI is well-positioned to address.  Among them are hospital and preventable medical error, as well as widespread administrative error, and the savings – estimated at $150 billion annually – that the healthcare sector could realize with the effective spread of AI programs.

But one particular segment of the healthcare sector that  . . . . says should benefit significantly from AI is medical imaging.

“Besides the fact that AI will result in improved accuracy of medical imaging diagnosis,” he argues, “it will also make it much easier to personalize treatment planning and transmit results. Not only will this enhance productivity in the radiologist community, but profitability can be attained sooner than expected.”

He adds that while AI was once viewed as a threat in the medical imaging community, those days are rapidly coming to a close.  Indeed, “demand for, and interest in, AI in the radiologist community has increased significantly in the recent past and investment in AI imaging technology is on the rise. . . .  In fact, research has revealed that there has been a rapid increase in capital investment in companies developing machine learning solutions for medical imaging in 2018. This trend is expected to continue well into 2019.”

Another area expected to benefit from AI is healthcare communication.  According to  . . . 

“(s)tatistics show that 80 percent of serious medical errors are due to miscommunication between caregivers during patient transfer. AI can, and will, more effectively address these communication issues.”

Similarly, he says, “effective application of AI to medical dosage error reduction can result in a savings of $16 billion for the healthcare industry by 2026. Medication and dosage errors are one of the leading causes of unanticipated but easily preventable death or serious injury in the healthcare industry today.”