The vast majority of implants brought to the operating room go unused during the surgery.
A new program—Supplies on Time—automates surgical case communication with vendors, ensuring accurate data for each case & reducing wasted cost and time for clinical teams.
https://t.co/HO7OnBZrGg
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: https://t.co/bvQJ1c5JK0
Colorectal cancer is one of the most diagnosed cancers in the United States, and it has become a leading cause of cancer-related death in young adults.
@UCDavisHealth implemented an AI tool into their electronic health record to automatically analyze colonoscopy reports and identify the number of precancerous polyps detected. Physicians can review their ADR compared to national and department averages and determine opportunities for improvement with their peers, helping improve clinical outcomes.