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Ten UCSF graduate students presented their research in accessible, 3-minute talks at the 2024 Grad Slam event. This year’s first-place talk was by Ilina Bhaya-Grossman on how our brains make meaning out of groups of vowels, consonants and pauses in our native tongues to recognize words.
The Allen Institute is the newest member of the Weill Neurohub, a collaborative research network advancing treatments for neurological diseases.
Artificial intelligence could potentially help extract liver tumor data at a much faster and accurate rate, setting possibilities for improved liver cancer care.
UCSF scientists found a way to predict Alzheimer’s disease up to seven years before symptoms appear by analyzing patient records with machine learning. Conditions that most influenced prediction of Alzheimer’s were high cholesterol and, for women, osteoporosis.
In a first, scientists at UCSF and Stanford identified genetic variants that predict whether a patient is likely to respond to treatment for preterm birth. Screening for mutations could allow doctors to target medications to those most likely to benefit. No medication is currently available in the U.S. to treat preterm birth.
A study of seriously ill patients from academic medical centers across the country has found that nearly a quarter had a delayed or missed diagnosis.
Could AI make nurses’ jobs – and our health care – better? Kay Burke, MBA, RN, who helps UCSF Health improve its digital tools, weighs in.
How a suite of advanced 3D technologies is ushering in surgery’s most sophisticated era yet.
It is clear the next year will be a pivotal one for UCSF’s place in the growth and application of artificial intelligence in health care. Chancellor Sam Hawgood, MBBS, spent a significant portion of
UC San Francisco is well positioned to transform into a global leader in artificial intelligence enabled academic life sciences. That was the message UCSF Chancellor Sam Hawgood, MBBS, delivered as
Bob Wachter comments on the potential of new generative artificial intelligence tools to transform the health care environment in a way previous technologies could not.
