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The impact that large language models have had both on the medical community and IT developers is undeniable. But are they being trained with the relevant data and the right kind of self-supervision? These are questions that need to be asked, according to Mayo Clinic Platform researchers.
Allowing stakeholders to access data while protecting patient rights remains a significant challenge. But there is a potential solution, according to Mayo Clinic Platform researchers, who describe a “federated approach” in which data are stored in encrypted containers.
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.
When leveraged for their original purpose – to “create a skeleton note for humans to augment and edit, reducing administrative burden – generative AI can help provide more time for patient care and clinical decision making, according to John Halamka, MD, and Paul Cerrato of Mayo Clinic Platform.
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.
