Asking medical questions of AI with language spoken “in the wild”—meaning with LLM prompts from everyday consumers—brings back answers with decidedly mediocre accuracy, a new study shows.
The Learning-based Inference of Longitudinal imAge Changes, or LILAC, system harnesses machine learning to review medical images that have been collected over a prolonged period.
Second-generation TAVR valves from Medtronic, Edwards Lifesciences and Boston Scientific are all associated with similar seven-year outcomes, according to a new retrospective study out of Italy.
“Unfortunately, the imbalance in available MIPS radiology measures is worsening,” said study co-author Lauren Nicola, MD, CEO of Triad Radiology Associates.
Asking medical questions of AI with language spoken “in the wild”—meaning with LLM prompts from everyday consumers—brings back answers with decidedly mediocre accuracy, a new study shows.
