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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.
Without the proper controls in place, AI-enabled algorithms can do more harm than good, according to researchers from Mayo Clinic Platform. In this piece, they explore how the new NIST framework can help leaders more accurately assess AI trustworthiness, explainability, and bias.
Despite the fact that CMS has extended the public health emergency that expanded telemedicine coverage, a number of states aren’t on board, according to Dr. John Halamka and Paul Cerrato. “Finding a way to extend the regulatory waivers,” they write, “is in our patients’ best interest.”
Physicians may never trust machine-learning-based algorithms completely. However, if developers provide right visualization tools, it may give them more confidence in an algorithm’s diagnostic and therapeutic skills, according to Paul Cerrato and John Halamka, MD.
