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Bringing together AI algorithms and data in ways that preserve privacy and intellectual property has long been a hurdle. Can software-based enclaves help clear it? Paul Cerrato and John Halamka, MD, of Mayo Clinic Platform have some thoughts.
Discovering evidence within the data doesn’t have much of an impact unless it can influence decision-making at the point of care, said Mark Hulse. In this podcast, he talks about how City of Hope is leveraging information to provide real-time guidance.
It’s hard to think that machines might do some tasks better than humans – especially clinicians who have trained for years to develop higher cortical skills. But they can, says Dr. Joseph Kvedar, especially when recognizing patterns in large data sets and using them to make predictions.
It’s not enough to provide evidence that AI tools are clinically effective; practitioners want reasonable explanations demonstrating that “they will do what they claim to do,” according to Dr. John Halamka and Paul Cerrato of Mayo Clinic Platform.
One way to help drive adoption of AI tools? Creating “a set of standards to help clinicians and other decision makers separate useful tools from junk science,” according to John Halamka, MD, and Paul Cerrato of Mayo Clinic Platform.
