08-03-2023, 03:52 AM
Artificial intelligence (AI) has long been touted as a game-changer in healthcare interoperability, but the hype surrounding it has left some providers unimpressed.
While there is no doubt that AI, also known as machine learning, holds great potential to revolutionize care delivery and business operations, exaggerated expectations, slick conference demonstrations, and lofty promises have yet to materialize in many affordable, real-world electronic health record (EHR) applications.
However, with the rise of generally available neural networks and advanced language models like ChatGPT and Bard, discussions about the role and scope of machine learning in healthcare have now, understandably, reached a fever pitch.
In this blog, we’ll try to separate science fiction from reality and highlight a few areas where hospital leaders can implement artificial intelligence right now to see tangible benefits.
More here.
While there is no doubt that AI, also known as machine learning, holds great potential to revolutionize care delivery and business operations, exaggerated expectations, slick conference demonstrations, and lofty promises have yet to materialize in many affordable, real-world electronic health record (EHR) applications.
However, with the rise of generally available neural networks and advanced language models like ChatGPT and Bard, discussions about the role and scope of machine learning in healthcare have now, understandably, reached a fever pitch.
In this blog, we’ll try to separate science fiction from reality and highlight a few areas where hospital leaders can implement artificial intelligence right now to see tangible benefits.
More here.