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In this episode, pioneering informatician Dr. Atul Butte guides listeners through his storied career, from his early days as a pediatric endocrinologist and informatician in Boston to his trailblazing work on the West Coast. Dr. Butte describes his trailblazing efforts to both harness large-scale public biomedical data and share patient data across the entire UC Health System. Dr. Butte also discusses his entrepreneurial journey, including the genesis and vision behind companies like NuMedii. Dr. Butte is the Priscilla Chan and Mark Zuckerberg Distinguished Professor at UCSF and the Chief Data Scientist of the UC Health System.

BCHSI faculty Tony Capra weighs in on this podcast: "Science has come to learn that one treatment plan or medication won’t work the same for every patient. We need to tailor every dosage and application specifically for each person to have the best results. Our expert this week explains that in order to move into this new era of medicine, we need to take a look back at our evolutionary path." 

28 talented high school students, most from California, participated in the 2023 virtual UCSF AI4ALL summer program and learned AI applications to Biomedicine with a focus on machine learning approaches.

JAMA announced on July 1, 2023, the appointment of Yulin Hswen, ScD, MPH, as an associate editor in artificial intelligence (AI) and medicine. Hswen joins the editorial board, where she will help guide the strategic direction for JAMA and the JAMA Network. 

Dr. Marina Sirota, principal investigator at the March of Dimes Prematurity Research Center at UCSF, and colleagues Dr. Tomiko Oskotsky and Dr. Jonathan Golob discuss using big data to launch a DREAM Challenge that succeeded in creating two predictive models for preterm birth risk.

BCHSI Sergio Barazini / Team Science effort: Scientists discover a genetic clue to why some people with MS become disabled faster than others.

The recording of this seminar is now available here via BOX - UCSF-access only.

UCSF BCHSI team published in JAMIA Open - Clinical notes are a veritable treasure trove of information on a patient’s disease progression, medical history, and treatment plans, yet are locked in secured databases accessible for research only after extensive ethics review.

The connection between concepts can be compared with curated biomedical KGs, such as UCSF’s SPOKE. 

Marina Sirota and Aleksandar Rajkovic co-lead / apply machine learning to mine EMR databases across CA and beyond in search of links between RPL clinical diagnoses and possible environmental risk factors

Bakar faculty Geoff Tison et al published about the AI algorithm provides novel information about cardiac pumping function (LVEF) from standard coronary angiograms.