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“Much of clinician burnout is due to spending time writing notes, placing orders, generating referrals, writing prior authorization letters, and creating patient communication. In other words, burnout is caused by physicians having to generate output! With the emergence of large language models that are used to train generative AI solutions, these use cases will be at the frontier of AI’s applications in healthcare.”

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Book:AI Doctor: The Rise of Artificial Intelligence in Healthcare - A Guide for Users, Buyers, Builders, and Investors
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“An algorithm that expedites care to a stroke patient in a chaotic emergency room (ER) has a good chance of adoption. An algorithm that reads a routine scan and provides some quantification of what the physicians can already estimate won’t be in as much demand. There are good reasons for algorithms to parse patient records to look for signs of rare diseases, but there are fewer good reasons for using them to evaluate clinical symptoms. It’s cool that AI tools can make diagnoses from scratch, but for most clinical encounters doctors are already pretty good at it.”

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Book:AI Doctor: The Rise of Artificial Intelligence in Healthcare - A Guide for Users, Buyers, Builders, and Investors
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