From the NEJM Catalyst event AI and Machine Learning for Health Care Delivery, sponsored by Advisory Board, March 24, 2022. In the special artificial intelligence theme issue of NEJM Catalyst Innovations in Care Delivery, "Preventing Delayed and Missed Care by Applying Artificial Intelligence to Trigger Radiology Imaging Follow-up" explores a Northwestern Medicine initiative that uses recurrent neural networks and natural language processing to examine radiology reports for findings necessitating follow-up. Speaking at the NEJM Catalyst "AI and Machine Learning for Health Care Delivery" event, senior author Mozziyar Etemadi, MD, PhD, describes the In Depth article. Most people outside of health care associate radiology with images from X-rays, CT scans, and MRIs. But to doctors who are not radiologists, what comes to mind are large blocks of text from radiology reports, which can be a lot to parse through, Etemadi says.

From the NEJM Catalyst event AI and Machine Learning for Health Care Delivery, sponsored by Advisory Board, March 24, 2022. In the special artificial intelligence theme issue of NEJM Catalyst Innovations in Care Delivery, "Using AI to Empower Collaborative Team Workflows: Two Implementations for Advance Care Planning and Care Escalation" compares AI implementations for improving the rate of advanced care planning and earlier prediction of clinical deterioration. Speaking at the NEJM Catalyst "AI and Machine Learning for Health Care Delivery" event, first author Ron C. Li, MD, describes the care escalation intervention and key takeaways from the case study. "Our work starts with a foundational premise: that we need to change how we think about AI in health care," says Li. Instead of starting with a machine learning model and then deciding how to deploy it, Li says that health care should start with a problem and think about AI not as the solution, but as a capability that enables a broader set of solutions. AI will not replace humans in health care, but empower them.

From the NEJM Catalyst event AI and Machine Learning for Health Care Delivery, sponsored by Advisory Board, March 24, 2022. In the special artificial intelligence theme issue of NEJM Catalyst Innovations in Care Delivery, "AI Insurance: How Liability Insurance Can Drive the Responsible Adoption of Artificial Intelligence in Health Care" explores how AI liability insurance can mitigate predictable risks and uncertainties to health care AI adoption. The big challenge for health care delivery is overcoming institutional mismatch, according to Stern. "The technologies that have the greatest potential to transform health care delivery --this includes, but is not limited, to AI -- would be unrecognizable to the 20th-century architects of our regulatory and health care delivery institutions," says Stern. "And this problem is getting worse. The pace of innovation that we see today coupled with our rapidly transforming analytical and technological capabilities is increasingly mismatched to our existing institutions."

From the NEJM Catalyst event AI and Machine Learning for Health Care Delivery, sponsored by Advisory Board, March 24, 2022. In the special artificial intelligence theme issue of NEJM Catalyst Innovations in Care Delivery, "How Health Systems Decide to Use Artificial Intelligence for Clinical Decision Support" explores how health systems decide which AI products to use. Speaking at the NEJM Catalyst "AI and Machine Learning for Health Care Delivery" event, senior author Christina Silcox, PhD, shares best practices for choosing health care AI tools. Potential for AI in the health space is enormous, from population health to individual health, health system administration, and biomedical innovation. Silcox and fellow researchers at the Duke-Margolis Center for Health Policy focused on how health systems choose which specific population and individual health tools to use.

A nurse avatar named "Molly" who regularly talks with patients about their symptoms and medical needs. Voice-recognition software that helps physicians document clinical encounters. A prescription drug-monitoring platform that can detect patients' opioid misuse. Systems that analyze millions of medical images to help physicians diagnose and predict diseases. Robots that extend the reach of surgeons.

"Mayo Clinic is embracing cognitive computing because we realize this technology is transformational and necessary for the continued evolution of health care delivery," says Nicholas F. LaRusso, M.D. Ask people what they know about Watson, IBM's cognitive computing system, and many might answer, "Didn't it cream those all-star contestants on Jeopardy a few years ago?" The answer is yes, it most certainly dealt Jeopardy champs Ken Jennings and Brad Rutter an ego-bruising defeat in 2011. So how did Watson do it? And how can this technology improve health care? Watson is artificial intelligence in action.