Shekoofeh Azizi
My research is focused on developing approaches that facilitate the translation of AI solutions into tangible clinical impact. I am particularly interested in designing foundation models for biomedical applications and have been leading a couple of major efforts in this area. I am one of the research leads driving the ambitious effort behind the creation of REMEDIES, Med-PaLM, Med-PaLM 2, Med-PaLM M, and Med-Gemini which are Google's flagship models, meticulously designed for medical applications.
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Google
An intentional approach to managing bias in embedding models
Atilla P. Kiraly
Jungyeon Park
Rory Pilgrim
Charles Lau
Heather Cole-Lewis
Shravya Shetty
Krish Eswaran
Leo Anthony Celi
The Lancet Digital Health, 6 (2024), E126-E130
Health AI Developer Foundations
Atilla Kiraly
Sebastien Baur
Kenneth Philbrick
Fereshteh Mahvar
Liron Yatziv
Tiffany Chen
Bram Sterling
Nick George
Fayaz Jamil
Jing Tang
Kai Bailey
Akshay Goel
Abbi Ward
Lin Yang
Shravya Shetty
Daniel Golden
Tim Thelin
Rory Pilgrim
Can "John" Kirmizi
arXiv (2024)
A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models
Heather Cole-Lewis
Nenad Tomašev
Liam McCoy
Leo Anthony Celi
Alanna Walton
Chirag Nagpal
Akeiylah DeWitt
Philip Mansfield
Sushant Prakash
Joelle Barral
Ivor Horn
Karan Singhal
Nature Medicine (2024)
Towards Conversational Diagnostic AI
Khaled Saab
Jan Freyberg
Ryutaro Tanno
Amy Wang
Brenna Li
Nenad Tomašev
Karan Singhal
Le Hou
Albert Webson
Kavita Kulkarni
Sara Mahdavi
Juro Gottweis
Joelle Barral
Kat Chou
Arxiv (2024) (to appear)
Towards Generalist Biomedical AI
Danny Driess
Andrew Carroll
Chuck Lau
Ryutaro Tanno
Ira Ktena
Basil Mustafa
Aakanksha Chowdhery
Simon Kornblith
Philip Mansfield
Sushant Prakash
Renee Wong
Sunny Virmani
Sara Mahdavi
Bradley Green
Ewa Dominowska
Joelle Barral
Karan Singhal
Pete Florence
NEJM AI (2024)
Generative models improve fairness of medical classifiers under distribution shifts
Ira Ktena
Olivia Wiles
Isabela Albuquerque
Sylvestre-Alvise Rebuffi
Ryutaro Tanno
Danielle Belgrave
Taylan Cemgil
Nature Medicine (2024)
Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging
Laura Anne Culp
Jan Freyberg
Basil Mustafa
Sebastien Baur
Simon Kornblith
Ting Chen
Patricia MacWilliams
Sara Mahdavi
Megan Zoë Walker
Aaron Loh
Cameron Chen
Scott Mayer McKinney
Jim Winkens
Zach William Beaver
Fiona Keleher Ryan
Mozziyar Etemadi
Umesh Telang
Lily Hao Yi Peng
Geoffrey Everest Hinton
Neil Houlsby
Mohammad Norouzi
Nature Biomedical Engineering (2023)
Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation
Ryutaro Tanno
David Barrett
Sumedh Ghaisas
Sumanth Dathathri
Abi See
Johannes Welbl
Karan Singhal
Rhys May
Roy Lee
SiWai Man
Zahra Ahmed
Sara Mahdavi
Joelle Barral
Ali Eslami
Danielle Belgrave
Shravya Shetty
Po-Sen Huang
Ira Ktena
Arxiv (2023)
Large Language Models Encode Clinical Knowledge
Karan Singhal
Sara Mahdavi
Jason Wei
Hyung Won Chung
Nathan Scales
Ajay Tanwani
Heather Cole-Lewis
Perry Payne
Martin Seneviratne
Paul Gamble
Christopher Kelly
Abubakr Abdelrazig Hassan Babiker
Nathanael Schaerli
Aakanksha Chowdhery
Philip Mansfield
Dina Demner-Fushman
Katherine Chou
Juraj Gottweis
Nenad Tomašev
Alvin Rajkomar
Joelle Barral
Nature (2023)
Towards Accurate Differential Diagnosis with Large Language Models
Daniel McDuff
Amy Wang
Karan Singhal
Yash Sharma
Kavita Kulkarni
Le Hou
Sara Mahdavi
Sushant Prakash
Anupam Pathak
Shwetak Patel
Ewa Dominowska
Juro Gottweis
Joelle Barral
Kat Chou
Jake Sunshine
Arxiv (2023)
