As AI continues to build momentum, a group of health systems, government agencies and tech companies are banding together to develop “a set of guidelines for safe, secure and trustworthy AI algorithms,” according to John Halamka, MD. In this blog, he outlines the five main objectives of the network.
Is the Future of AI in Good Hands?
“A Profound Impact”: How NLP Fits into the Digital Health Ecosystem
“A Step in the Right Direction”: How Prompt Engineering Can Improve GenAI
Generative AI Benefits: We’ve Barely Scratched the Surface
“Data Behind Glass”: Exploring a Federated Model for Data Management
“Untapped Power”: The Critical Role Digital Tools Can Play in Addressing Social Determinants
Addressing health inequities is going to require systemic changes in national policies. In the meantime, however, “there are measures that clinicians and technologists can implement that will have an impact,” according to John Halamka, MD, who discusses how Mayo Clinic is working to create AI platforms and algorithms to change outcomes.
Is It Time to Incorporate Large Language Models into EHRs?
“Proceed with Humility”: The Keys to Moving Forward with Generative AI
Large language models offer great potential for improving care and efficiency, but “that must be done within guardrails and guidelines so that we do no digital harm,” said Paul Cerrato and John Halamka, MD. In this piece, they discuss the key components for successful development and deployment of AI tools.