Collaborating Authors

AWS on AI, machine learning, interoperability improving patient outcomes


As the country moves toward value-based care, artificial intelligence and machine learning – paired with data interoperability – have the potential to improve patient outcomes while driving operational efficiency to lower the overall cost of care. By enabling interoperability securely and supporting healthcare providers with predictive machine learning models and insights afforded by genomic research, clinicians will be able to seamlessly forecast clinical events – such as strokes, cancer or heart attacks – and intervene early with personalized care and access to curated information to support a superior patient experience. Further powering these predictive capabilities with location-agnostic, voice-enabled, accessible modalities of providing care advances the practice of medicine to align with what is most convenient, affordable and targeted for the specific needs of patients. Healthcare IT News sat down with Phoebe Yang, general manager for non-profit healthcare at Amazon Web Services, to discuss these subjects, offering healthcare CIOs and other health IT leaders lessons in state-of-the-art technologies. How can AI and machine learning combined with data interoperability enhance patient outcomes and operational efficiency to lower care costs? A. Interoperability among medical information systems is foundational – or should be – because without it, physicians don't have ready access to their patients' complete medical histories.

Q/A: Life Image CEO Talks Data Sharing Challenges in Breast Imaging


Interoperability--it's the long-awaited result that evolving HIT promised to bring with it, and yet, it still gets left behind. Disparate data is not a problem exclusive to one data type or innovation; breast imaging, for example, has created some of the toughest challenges. However, there is now an app for that. Life Image, which was founded in 2008, formed to overcome some of those interoperability challenges posed by the U.S. healthcare and evolving tech landscape. Since then, according to its President and CEO Matthew Michaela, the Newton, MA-based company has built a large global medical evidence network through a combination of technical expertise and unrelenting effort in the face of the many barriers that often stymie healthcare.

Medical imaging, AI, and the cloud: what's next? - Microsoft Industry Blogs


Today marks the start of RSNA 2020, the annual meeting of the Radiological Society of North America. I participated in my first RSNA 35 years ago and I am super excited--as I am every year--to reconnect with my radiology colleagues and friends and learn about the latest medical and scientific advances in our field. Of course, RSNA will be very different this year. Instead of traveling to Chicago to attend sessions and presentations, and wander the exhibits, I'll experience it all online. While I will miss the fun, excitement, and opportunities to connect that come with being there in person, I am amazed by what a rich and comprehensive conference the organizers of RSNA 2020 have put together using the advanced digital tools that we have at hand now.

For Hyland, interoperability, clinical AI and cloud adoption are the HIMSS20 trends to watch


Hyland, a vendor of content services and enterprise imaging technologies, will have a major presence at the HIMSS20 Global Conference. It's a big player in healthcare information technology, and has a team with decades of experience in the industry. Ahead of HIMSS20, Healthcare IT News interviewed Susan deCathelineau, senior vice president of healthcare sales and services at Hyland. She offers her perspective on the key trends impacting conference attendees. She identifies interoperability, AI for clinical uses, and providers finally embracing the cloud as three trends that healthcare CIOs and other health IT leaders should be on top of.

How Artificial Intelligence and Blockchain Can Reshape Healthcare Industry?


Ninety-four percent of healthcare executives report that artificial intelligence, blockchain, and other emerging technologies have accelerated the pace of innovation over the past three years, according to an Accenture report. However, the report also found that while technology investments have progressed, healthcare organizations still need to do more to meet rising consumer and employee expectations. The healthcare industry has largely come to recognize that digital technologies must be a core part of everyday processes, with organizations increasingly investing in social, mobile, analytics, and cloud technologies. Eighty percent of healthcare executives agreed that these tools have moved beyond adoption silos to become an integral part of the technology foundation of their organizations. Here is how AI, ML, and blockchain are reshaping the healthcare industry.