Researchers at @Yale using Curiosity—Epic's generative medical event model, which simulates a patient's likely future course from their record — looked at adults discharged from the ED with abdominal pain, one of the most common and most uncertain presentations in emergency medicine. Traditional risk models answer a binary question: will this patient come back? Curiosity answers a richer one: if they return, when, and will that return end in discharge or admission? Two patients can carry the same overall revisit probability but face very different paths—one headed toward a quick outpatient follow-up, another toward an early admission. A binary score flattens that difference. A trajectory surfaces it. A single pretrained model, like Curiosity, can generate calibrated predictions across many outcomes without retraining. As a result, the focus and time shift away from building a bespoke model for every clinical question and toward deciding which questions are worth asking. The team moved from idea to results in a matter of weeks. It also highlights an emerging skillset: clinicians who pair deep clinical reasoning with real fluency in generative AI. The questions they choose to ask are the key ingredient. Preprint here: medrxiv.org/content/10.64898…

Imagining a thoughtfully curated, hard-bound book (a la @stripepress) collecting the essential essays and papers demonstrating how society dealt with this moment in AI. Trying to compile what truly deserves to make the cut.