Dale R. Webster

According to our database, Dale R. Webster authored at least 31 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Towards Democratization of Subspeciality Medical Expertise.

Jack W. O'Sullivan, Anil Palepu, Khaled Saab, Wei-Hung Weng, Yong Cheng, Emily Chu, Yaanik Desai, Aly Elezaby, Daniel Seung Kim, Roy Lan, Wilson Tang, Natalie Tapaskar, Victoria Parikh, Sneha S. Jain, Kavita Kulkarni, Philip Mansfield, Dale R. Webster, Juraj Gottweis, Joelle Barral, Mike Schaekermann, Ryutaro Tanno, S. Sara Mahdavi, Vivek Natarajan, Alan Karthikesalingam, Euan Ashley, Tao Tu

CoRR, 2024

PathAlign: A vision-language model for whole slide images in histopathology.

Faruk Ahmed, Andrew Sellergren, Lin Yang, Shawn Xu, Boris Babenko, Abbi Ward, Niels Olson, Arash Mohtashamian, Yossi Matias, Greg Corrado, Quang Duong, Dale R. Webster, Shravya Shetty, Daniel Golden, Yun Liu, David F. Steiner, Ellery Wulczyn

CoRR, 2024

Capabilities of Gemini Models in Medicine.

Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G. T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-Baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Benjamin Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Andrew Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale R. Webster, Joelle K. Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan

CoRR, 2024

Crowdsourcing Dermatology Images with Google Search Ads: Creating a Real-World Skin Condition Dataset.

Abbi Ward, Jimmy Li, Julie Wang, Sriram Lakshminarasimhan, Ashley Carrick, Bilson J. L. Campana, Jay Hartford, Pradeep Kumar S, Tiya Tiyasirichokchai, Sunny Virmani, Renee Wong, Yossi Matias, Gregory S. Corrado, Dale R. Webster, Dawn Siegel, Steven Lin, Justin Ko, Alan Karthikesalingam, Christopher Semturs, Pooja Rao

CoRR, 2024

Closing the AI generalization gap by adjusting for dermatology condition distribution differences across clinical settings.

Rajeev V. Rikhye, Aaron Loh, Grace Eunhae Hong, Preeti Singh, Margaret Ann Smith, Vijaytha Muralidharan, Doris Wong, Rory Sayres, Michelle Phung, Nicolas Betancourt, Bradley Fong, Rachna Sahasrabudhe, Khoban Nasim, Alec Eschholz, Basil Mustafa, Jan Freyberg, Terry Spitz, Yossi Matias, Gregory S. Corrado, Katherine Chou, Dale R. Webster, Peggy Bui, Yuan Liu, Yun Liu, Justin Ko, Steven Lin

CoRR, 2024

MINT: A wrapper to make multi-modal and multi-image AI models interactive.

Jan Freyberg, Abhijit Guha Roy, Terry Spitz, Beverly Freeman, Mike Schaekermann, Patricia Strachan, Eva Schnider, Renee Wong, Dale R. Webster, Alan Karthikesalingam, Yun Liu, Krishnamurthy Dvijotham, Umesh Telang

CoRR, 2024

Conversational AI in health: Design considerations from a Wizard-of-Oz dermatology case study with users, clinicians and a medical LLM.

Brenna Li, Amy Wang, Patricia Strachan, Julie Anne Séguin, Sami Lachgar, Karyn C. Schroeder, Mathias S. Fleck, Renee Wong, Alan Karthikesalingam, Vivek Natarajan, Yossi Matias, Gregory S. Corrado, Dale R. Webster, Yun Liu, Naama Hammel, Rory Sayres, Christopher Semturs, Mike Schaekermann

Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024

2023

Towards Accurate Differential Diagnosis with Large Language Models.

Daniel McDuff, Mike Schaekermann, Tao Tu, Anil Palepu, Amy Wang, Jake Garrison, Karan Singhal, Yash Sharma, Shekoofeh Azizi, Kavita Kulkarni, Le Hou, Yong Cheng, Yun Liu, S. Sara Mahdavi, Sushant Prakash, Anupam Pathak, Christopher Semturs, Shwetak N. Patel, Dale R. Webster, Ewa Dominowska, Juraj Gottweis, Joelle K. Barral, Katherine Chou, Gregory S. Corrado, Yossi Matias, Jake Sunshine, Alan Karthikesalingam, Vivek Natarajan

CoRR, 2023

Domain-specific optimization and diverse evaluation of self-supervised models for histopathology.

Jeremy Lai, Faruk Ahmed, Supriya Vijay, Tiam Jaroensri, Jessica Loo, Saurabh Vyawahare, Saloni Agarwal, Fayaz Jamil, Yossi Matias, Gregory S. Corrado, Dale R. Webster, Jonathan Krause, Yun Liu, Po-Hsuan Cameron Chen, Ellery Wulczyn, David F. Steiner

CoRR, 2023

Towards Generalist Biomedical AI.

Tao Tu, Shekoofeh Azizi, Danny Driess, Mike Schaekermann, Mohamed Amin, Pi-Chuan Chang, Andrew Carroll, Chuck Lau, Ryutaro Tanno, Ira Ktena, Basil Mustafa, Aakanksha Chowdhery, Yun Liu, Simon Kornblith, David J. Fleet, Philip Andrew Mansfield, Sushant Prakash, Renee Wong, Sunny Virmani, Christopher Semturs, S. Sara Mahdavi, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Joelle K. Barral, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Karan Singhal, Pete Florence, Alan Karthikesalingam, Vivek Natarajan

CoRR, 2023

Evaluating AI systems under uncertain ground truth: a case study in dermatology.

David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy, Tatiana Matejovicova, Melih Barsbey, Patricia Strachan, Mike Schaekermann, Jan Freyberg, Rajeev V. Rikhye, Beverly Freeman, Javier Perez Matos, Umesh Telang, Dale R. Webster, Yuan Liu, Gregory S. Corrado, Yossi Matias, Pushmeet Kohli, Yun Liu, Arnaud Doucet, Alan Karthikesalingam

CoRR, 2023

Using generative AI to investigate medical imagery models and datasets.

Oran Lang, Doron Yaya-Stupp, Ilana Traynis, Heather Cole-Lewis, Chloe R. Bennett, Courtney Lyles, Charles Lau, Christopher Semturs, Dale R. Webster, Gregory S. Corrado, Avinatan Hassidim, Yossi Matias, Yun Liu, Naama Hammel, Boris Babenko

CoRR, 2023

Towards Expert-Level Medical Question Answering with Large Language Models.

Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Le Hou, Kevin Clark, Stephen Pfohl, Heather Cole-Lewis, Darlene Neal, Mike Schaekermann, Amy Wang, Mohamed Amin, Sami Lachgar, Philip Andrew Mansfield, Sushant Prakash, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Nenad Tomasev, Yun Liu, Renee Wong, Christopher Semturs, S. Sara Mahdavi, Joelle K. Barral, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Shekoofeh Azizi, Alan Karthikesalingam, Vivek Natarajan

CoRR, 2023

2022

Large Language Models Encode Clinical Knowledge.

Karan Singhal, Shekoofeh Azizi, Tao Tu, S. Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Kumar Tanwani, Heather Cole-Lewis, Stephen Pfohl, Perry Payne, Martin Seneviratne, Paul Gamble, Chris Kelly, Nathaneal Schärli, Aakanksha Chowdhery, Philip Andrew Mansfield, Blaise Agüera y Arcas, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Katherine Chou, Juraj Gottweis, Nenad Tomasev, Yun Liu, Alvin Rajkomar, Joelle K. Barral, Christopher Semturs, Alan Karthikesalingam, Vivek Natarajan

CoRR, 2022

Discovering novel systemic biomarkers in photos of the external eye.

Boris Babenko, Ilana Traynis, Christina Chen, Preeti Singh, Akib Uddin, Jorge Cuadros, Lauren P. Daskivich, April Y. Maa, Kim Ramasamy, Eugene Yu-Chuan Kang, Yossi Matias, Gregory S. Corrado, Lily Peng, Dale R. Webster, Christopher Semturs, Jonathan Krause, Avinash V. Varadarajan, Naama Hammel, Yun Liu

CoRR, 2022

Robust and Efficient Medical Imaging with Self-Supervision.

Shekoofeh Azizi, Laura Culp, Jan Freyberg, Basil Mustafa, Sebastien Baur, Simon Kornblith, Ting Chen, Patricia MacWilliams, S. Sara Mahdavi, Ellery Wulczyn, Boris Babenko, Megan Wilson, Aaron Loh, Po-Hsuan Cameron Chen, Yuan Liu, Pinal Bavishi, Scott Mayer McKinney, Jim Winkens, Abhijit Guha Roy, Zachary Beaver, Fiona Ryan, Justin Krogue, Mozziyar Etemadi, Umesh Telang, Yun Liu, Lily Peng, Gregory S. Corrado, Dale R. Webster, David J. Fleet, Geoffrey E. Hinton, Neil Houlsby, Alan Karthikesalingam, Mohammad Norouzi, Vivek Natarajan

CoRR, 2022

2020

Detecting hidden signs of diabetes in external eye photographs.

Boris Babenko, Akinori Mitani, Ilana Traynis, Naho Kitade, Preeti Singh, April Y. Maa, Jorge Cuadros, Greg Corrado, Lily Peng, Dale R. Webster, Avinash V. Varadarajan, Naama Hammel, Yun Liu

CoRR, 2020

Predicting Risk of Developing Diabetic Retinopathy using Deep Learning.

Ashish Bora, Siva Balasubramanian, Boris Babenko, Sunny Virmani, Subhashini Venugopalan, Akinori Mitani, Guilherme de Oliveira Marinho, Jorge Cuadros, Paisan Ruamviboonsuk, Gregory S. Corrado, Lily Peng, Dale R. Webster, Avinash V. Varadarajan, Naama Hammel, Yun Liu, Pinal Bavishi

CoRR, 2020

Scientific Discovery by Generating Counterfactuals using Image Translation.

Arunachalam Narayanaswamy, Subhashini Venugopalan, Dale R. Webster, Lily Peng, Greg Corrado, Paisan Ruamviboonsuk, Pinal Bavishi, Rory Sayres, Abigail E. Huang, Siva Balasubramanian, Michael P. Brenner, Philip Q. Nelson, Avinash V. Varadarajan

CoRR, 2020

Scientific Discovery by Generating Counterfactuals Using Image Translation.

Arunachalam Narayanaswamy, Subhashini Venugopalan, Dale R. Webster, Lily Peng, Gregory S. Corrado, Paisan Ruamviboonsuk, Pinal Bavishi, Michael P. Brenner, Philip C. Nelson, Avinash V. Varadarajan

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019

Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program.

Paisan Ruamviboonsuk, Jonathan Krause, Peranut Chotcomwongse, Rory Sayres, Rajiv Raman, Kasumi Widner, Bilson J. L. Campana, Sonia Phene, Kornwipa Hemarat, Mongkol Tadarati, Sukhum Silpa-Archa, Jirawut Limwattanayingyong, Chetan Rao, Oscar Kuruvilla, Jesse Jung, Jeffrey Tan, Surapong Orprayoon, Chawawat Kangwanwongpaisan, Ramase Sukulmalpaiboon, Chainarong Luengchaichawang, Jitumporn Fuangkaew, Pipat Kongsap, Lamyong Chualinpha, Sarawuth Saree, Srirat Kawinpanitan, Korntip Mitvongsa, Siriporn Lawanasakol, Chaiyasit Thepchatri, Lalita Wongpichedchai, Gregory S. Corrado, Lily Peng, Dale R. Webster

npj Digit. Medicine, 2019

Author Correction: Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program.

Paisan Ruamviboonsuk, Jonathan Krause, Peranut Chotcomwongse, Rory Sayres, Rajiv Raman, Kasumi Widner, Bilson J. L. Campana, Sonia Phene, Kornwipa Hemarat, Mongkol Tadarati, Sukhum Silpa-Archa, Jirawut Limwattanayingyong, Chetan Rao, Oscar Kuruvilla, Jesse Jung, Jeffrey Tan, Surapong Orprayoon, Chawawat Kangwanwongpaisan, Ramase Sukulmalpaiboon, Chainarong Luengchaichawang, Jitumporn Fuangkaew, Pipat Kongsap, Lamyong Chualinpha, Sarawuth Saree, Srirat Kawinpanitan, Korntip Mitvongsa, Siriporn Lawanasakol, Chaiyasit Thepchatri, Lalita Wongpichedchai, Gregory S. Corrado, Lily Peng, Dale R. Webster

npj Digit. Medicine, 2019

A deep learning system for differential diagnosis of skin diseases.

Yuan Liu, Ayush Jain, Clara Eng, David H. Way, Kang Lee, Peggy Bui, Kimberly Kanada, Guilherme de Oliveira Marinho, Jessica Gallegos, Sara Gabriele, Vishakha Gupta, Nalini Singh, Vivek Natarajan, Rainer Hofmann-Wellenhof, Gregory S. Corrado, Lily H. Peng, Dale R. Webster, Dennis Ai, Susan Huang, Yun Liu, R. Carter Dunn, David Coz

CoRR, 2019

Detecting Anemia from Retinal Fundus Images.

Akinori Mitani, Yun Liu, Abigail E. Huang, Gregory S. Corrado, Lily Peng, Dale R. Webster, Naama Hammel, Avinash V. Varadarajan

CoRR, 2019

Predicting Progression of Age-related Macular Degeneration from Fundus Images using Deep Learning.

Boris Babenko, Siva Balasubramanian, Katy E. Blumer, Gregory S. Corrado, Lily Peng, Dale R. Webster, Naama Hammel, Avinash V. Varadarajan

CoRR, 2019

2018

Deep Learning to Assess Glaucoma Risk and Associated Features in Fundus Images.

Sonia Phene, R. Carter Dunn, Naama Hammel, Yun Liu, Jonathan Krause, Naho Kitade, Mike Schaekermann, Rory Sayres, Derek J. Wu, Ashish Bora, Christopher Semturs, Anita Misra, Abigail E. Huang, Arielle Spitze, Felipe A. Medeiros, April Y. Maa, Monica Gandhi, Gregory S. Corrado, Lily Peng, Dale R. Webster

CoRR, 2018

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning.

Avinash V. Varadarajan, Pinal Bavishi, Paisan Raumviboonsuk, Peranut Chotcomwongse, Subhashini Venugopalan, Arunachalam Narayanaswamy, Jorge Cuadros, Kuniyoshi Kanai, George Bresnick, Mongkol Tadarati, Sukhum Silpa-Archa, Jirawut Limwattanayingyong, Variya Nganthavee, Joe Ledsam, Pearse A. Keane, Gregory S. Corrado, Lily Peng, Dale R. Webster

CoRR, 2018

Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening Program.

Paisan Raumviboonsuk, Jonathan Krause, Peranut Chotcomwongse, Rory Sayres, Rajiv Raman, Kasumi Widner, Bilson J. L. Campana, Sonia Phene, Kornwipa Hemarat, Mongkol Tadarati, Sukhum Silpa-Archa, Jirawut Limwattanayingyong, Chetan Rao, Oscar Kuruvilla, Jesse Jung, Jeffrey Tan, Surapong Orprayoon, Chawawat Kangwanwongpaisan, Ramase Sukulmalpaiboon, Chainarong Luengchaichawang, Jitumporn Fuangkaew, Pipat Kongsap, Lamyong Chualinpha, Sarawuth Saree, Srirat Kawinpanitan, Korntip Mitvongsa, Siriporn Lawanasakol, Chaiyasit Thepchatri, Lalita Wongpichedchai, Gregory S. Corrado, Lily Peng, Dale R. Webster

CoRR, 2018

2017

Deep learning for predicting refractive error from retinal fundus images.

Avinash V. Varadarajan, Ryan Poplin, Katy Blumer, Christof Angermüller, Joe Ledsam, Reena Chopra, Pearse A. Keane, Greg Corrado, Lily Peng, Dale R. Webster

CoRR, 2017

Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy.

Jonathan Krause, Varun Gulshan, Ehsan Rahimy, Peter Karth, Kasumi Widner, Gregory S. Corrado, Lily Peng, Dale R. Webster

CoRR, 2017

Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs using Deep Learning.

Ryan Poplin, Avinash V. Varadarajan, Katy Blumer, Yun Liu, Michael V. McConnell, Gregory S. Corrado, Lily Peng, Dale R. Webster

CoRR, 2017