Gregory S. Corrado

According to our database, Gregory S. Corrado authored at least 76 papers between 2009 and 2025.

Collaborative distances:

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

2025

PolyPath: Adapting a Large Multimodal Model for Multi-slide Pathology Report Generation.

Faruk Ahmed, Lin Yang, Tiam Jaroensri, Andrew Sellergren, Yossi Matias, Avinatan Hassidim, Gregory S. Corrado, Dale R. Webster, Shravya Shetty, Shruthi Prabhakara, Yun Liu, Daniel Golden, Ellery Wulczyn, David F. Steiner

CoRR, February, 2025

Evaluating medical AI systems in dermatology under uncertain ground truth.

David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy, Tatiana Matejovicova, Melih Barsbey, Patricia Strachan, Mike Schaekermann, Jan Freyberg, Rajeev 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

Medical Image Anal., 2025

Navigating Skin Concerns with AI: A Human-Centered Investigation of a Dermatology App in a Diverse Community.

Rory Sayres, Anna Devon-Sand, Mike Schaekermann, Margaret Ann Smith, Patricia Strachan, Grace Eunhae Hong, Trinh Nguyen, Doris Wong, Naama Hammel, Dawn Siegel, Kexin Ren, Chelsea Belletieri, Vijaytha Muralidharan, Rajeev Rikhye, Yuan Liu, Beverly Freeman, Mike González, Nathan Ashcraft, Heidi Cho, Jimmy Li, Shweta Oak, Megan Shum, Abbi Ward, Yossi Matias, Gregory S. Corrado, Dale R. Webster, Peggy Bui, Preeti Singh, Yun Liu, Justin Ko, Steven Lin

Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2025

2024

General Geospatial Inference with a Population Dynamics Foundation Model.

Mohit Agarwal, Mimi Sun, Chaitanya Kamath, Arbaaz Muslim, Prithul Sarker, Joydeep Paul, Hector Yee, Marcin Sieniek, Kim Philipp Jablonski, Yael Mayer, David Fork, Sheila de Guia, Jamie McPike, Adam Boulanger, Tomer Shekel, David Schottlander, Yao Xiao, Manjit Chakravarthy Manukonda, Yun Liu, Neslihan Bulut, Sami Abu-el-haija, Arno Eigenwillig, Parth Kothari, Bryan Perozzi, Monica Bharel, Von Nguyen, Luke Barrington, Niv Efron, Yossi Matias, Greg Corrado, Krish Eswaran, Shruthi Prabhakara, Shravya Shetty, Gautam Prasad

CoRR, 2024

Towards a Personal Health Large Language Model.

Justin Cosentino, Anastasiya Belyaeva, Xin Liu, Nicholas A. Furlotte, Zhun Yang, Chace Lee, Erik Schenck, Yojan Patel, Jian Cui, Logan Douglas Schneider, Robby Bryant, Ryan G. Gomes, Allen Jiang, Roy Lee, Yun Liu, Javier Perez Matos, Jameson K. Rogers, Cathy Speed, Shyam A. Tailor, Megan Walker, Jeffrey Yu, Tim Althoff, Conor Heneghan, John Hernandez, Mark Malhotra, Leor Stern, Yossi Matias, Gregory S. Corrado, Shwetak N. Patel, Shravya Shetty, Jiening Zhan, Shruthi Prabhakara, Daniel McDuff, Cory Y. McLean

CoRR, 2024

Advancing Multimodal Medical Capabilities of Gemini.

Lin Yang, Shawn Xu, Andrew Sellergren, Timo Kohlberger, Yuchen Zhou, Ira Ktena, Atilla P. Kiraly, Faruk Ahmed, Farhad Hormozdiari, Tiam Jaroensri, Eric Wang, Ellery Wulczyn, Fayaz Jamil, Theo Guidroz, Chuck Lau, Siyuan Qiao, Yun Liu, Akshay Goel, Kendall Park, Arnav Agharwal, Nick George, Yang Wang, Ryutaro Tanno, David G. T. Barrett, Wei-Hung Weng, S. Sara Mahdavi, Khaled Saab, Tao Tu, Sreenivasa Raju Kalidindi, Mozziyar Etemadi, Jorge Cuadros, Gregory Sorensen, Yossi Matias, Katherine Chou, Greg Corrado, Joelle K. Barral, Shravya Shetty, David J. Fleet, S. M. Ali Eslami, Daniel Tse, Shruthi Prabhakara, Cory Y. McLean, Dave Steiner, Rory Pilgrim, Christopher Kelly, Shekoofeh Azizi, Daniel Golden

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

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models.

Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres, Darlene Neal, Mercy Nyamewaa Asiedu, Awa Dieng, Nenad Tomasev, Qazi Mamunur Rashid, Shekoofeh Azizi, Negar Rostamzadeh, Liam G. McCoy, Leo Anthony Celi, Yun Liu, Mike Schaekermann, Alanna Walton, Alicia Parrish, Chirag Nagpal, Preeti Singh, Akeiylah Dewitt, Philip Andrew Mansfield, Sushant Prakash, Katherine A. Heller, Alan Karthikesalingam, Christopher Semturs, Joelle K. Barral, Greg Corrado, Yossi Matias, Jamila Smith-Loud, Ivor Horn, Karan Singhal

CoRR, 2024

HeAR - Health Acoustic Representations.

Sebastien Baur, Zaid Nabulsi, Wei-Hung Weng, Jake Garrison, Louis Blankemeier, Sam Fishman, Christina Chen, Sujay Kakarmath, Minyoi Maimbolwa, Nsala Sanjase, Brian Shuma, Yossi Matias, Gregory S. Corrado, Shwetak N. Patel, Shravya Shetty, Shruthi Prabhakara, Monde Muyoyeta, Diego Ardila

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

Towards Conversational Diagnostic AI.

Tao Tu, Anil Palepu, Mike Schaekermann, Khaled Saab, Jan Freyberg, Ryutaro Tanno, Amy Wang, Brenna Li, Mohamed Amin, Nenad Tomasev, Shekoofeh Azizi, Karan Singhal, Yong Cheng, Le Hou, Albert Webson, Kavita Kulkarni, S. Sara Mahdavi, Christopher Semturs, Juraj Gottweis, Joelle K. Barral, Katherine Chou, Gregory S. Corrado, Yossi Matias, Alan Karthikesalingam, Vivek Natarajan

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, Gregory S. Corrado, Quang Duong, Dale R. Webster, Shravya Shetty, Daniel Golden, Yun Liu, David F. Steiner, Ellery Wulczyn

Proceedings of the MICCAI Workshop on Computational Pathology, 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

ELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders.

Shawn Xu, Lin Yang, Christopher Kelly, Marcin Sieniek, Timo Kohlberger, Martin Ma, Wei-Hung Weng, Attila Kiraly, Sahar Kazemzadeh, Zakkai Melamed, Jungyeon Park, Patricia Strachan, Yun Liu, Chuck Lau, Preeti Singh, Christina Chen, Mozziyar Etemadi, Sreenivasa Raju Kalidindi, Yossi Matias, Katherine Chou, Gregory S. Corrado, Shravya Shetty, Daniel Tse, Shruthi Prabhakara, Daniel Golden, Rory Pilgrim, Krish Eswaran, Andrew Sellergren

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

Predicting Cardiovascular Disease Risk using Photoplethysmography and Deep Learning.

Wei-Hung Weng, Sebastien Baur, Mayank Daswani, Christina Chen, Lauren Harrell, Sujay Kakarmath, Mariam Jabara, Babak Behsaz, Cory Y. McLean, Yossi Matias, Gregory S. Corrado, Shravya Shetty, Shruthi Prabhakara, Yun Liu, Goodarz Danaei, Diego Ardila

CoRR, 2023

Multimodal LLMs for Health Grounded in Individual-Specific Data.

Anastasiya Belyaeva, Justin Cosentino, Farhad Hormozdiari, Krish Eswaran, Shravya Shetty, Greg Corrado, Andrew Carroll, Cory Y. McLean, Nicholas A. Furlotte

Proceedings of the Machine Learning for Multimodal Healthcare Data, 2023

2022

Does your dermatology classifier know what it doesn't know? Detecting the long-tail of unseen conditions.

Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, Yuan Liu, Zachary Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Gregory S. Corrado, Umesh Telang, Yun Liu, A. Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens

Medical Image Anal., 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

AI system for fetal ultrasound in low-resource settings.

Ryan G. Gomes, Bellington Vwalika, Chace Lee, Angelica Willis, Marcin Sieniek, Joan T. Price, Christina Chen, Margaret P. Kasaro, James A. Taylor, Elizabeth M. Stringer, Scott Mayer McKinney, Ntazana Sindano, George E. Dahl, William Goodnight III, Justin Gilmer, Benjamin H. Chi, Charles Lau, Terry Spitz, T. Saensuksopa, Kris Liu, Jonny Wong, Rory Pilgrim, Akib Uddin, Greg Corrado, Lily Peng, Katherine Chou, Daniel Tse, Jeffrey S. A. Stringer, Shravya Shetty

CoRR, 2022

2021

Interpretable survival prediction for colorectal cancer using deep learning.

Ellery Wulczyn, David F. Steiner, Melissa Moran, Markus Plass, Robert Reihs, Fraser Tan, Isabelle Flament-Auvigne, Trissia Brown, Peter Regitnig, Po-Hsuan Cameron Chen, Narayan Hegde, Apaar Sadhwani, Robert MacDonald, Benny Ayalew, Gregory S. Corrado, Lily H. Peng, Daniel Tse, Heimo Müller, Zhaoyang Xu, Yun Liu, Martin C. Stumpe, Kurt Zatloukal, Craig H. Mermel

npj Digit. Medicine, 2021

Vaccine Search Patterns Provide Insights into Vaccination Intent.

Sean Malahy, Mimi Sun, Keith Spangler, Jessica Leibler, Kevin Lane, Shailesh Bavadekar, Chaitanya Kamath, Akim Kumok, Yuantong Sun, Jai Gupta, Tague Griffith, Adam Boulanger, Mark Young, Charlotte Stanton, Yael Mayer, Karen Smith, Tomer Shekel, Katherine Chou, Greg Corrado, Jonathan Levy, Adam Szpiro, Evgeniy Gabrilovich, Gregory A. Wellenius

CoRR, 2021

Deep learning for detecting pulmonary tuberculosis via chest radiography: an international study across 10 countries.

Sahar Kazemzadeh, Jin Yu, Shahar Jamshy, Rory Pilgrim, Zaid Nabulsi, Christina Chen, Neeral Beladia, Charles Lau, Scott Mayer McKinney, Thad Hughes, Atilla P. Kiraly, Sreenivasa Raju Kalidindi, Monde Muyoyeta, Jameson Malemela, Ting Shih, Gregory S. Corrado, Lily Peng, Katherine Chou, Po-Hsuan Cameron Chen, Yun Liu, Krish Eswaran, Daniel Tse, Shravya Shetty, Shruthi Prabhakara

CoRR, 2021

2020

Detecting Deficient Coverage in Colonoscopies.

Daniel Freedman, Yochai Blau, Liran Katzir, Amit Aides, Ilan Shimshoni, Danny Veikherman, Tomer Golany, Ariel Gordon, Greg Corrado, Yossi Matias, Ehud Rivlin

IEEE Trans. Medical Imaging, 2020

Customization scenarios for de-identification of clinical notes.

Tzvika Hartman, Michael D. Howell, Jeff Dean, Shlomo Hoory, Ronit Slyper, Itay Laish, Oren Gilon, Danny Vainstein, Greg Corrado, Katherine Chou, Ming Jack Po, Jutta Williams, Scott Ellis, Gavin Bee, Avinatan Hassidim, Rony Amira, Genady Beryozkin, Idan Szpektor, Yossi Matias

BMC Medical Informatics Decis. Mak., 2020

Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading.

Ellery Wulczyn, Kunal Nagpal, Matthew Symonds, Melissa Moran, Markus Plass, Robert Reihs, Farah Nader, Fraser Tan, Yuannan Cai, Trissia Brown, Isabelle Flament-Auvigne, Mahul B. Amin, Martin C. Stumpe, Heimo Müller, Peter Regitnig, Andreas Holzinger, Gregory S. Corrado, Lily H. Peng, Po-Hsuan Cameron Chen, David F. Steiner, Kurt Zatloukal, Yun Liu, Craig H. Mermel

CoRR, 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

Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases.

Zaid Nabulsi, Andrew Sellergren, Shahar Jamshy, Charles Lau, Eddie Santos, Atilla P. Kiraly, Wenxing Ye, Jie Yang, Sahar Kazemzadeh, Jin Yu, Raju Kalidindi, Mozziyar Etemadi, Florencia Garcia Vicente, David S. Melnick, Gregory S. Corrado, Lily Peng, Krish Eswaran, Daniel Tse, Neeral Beladia, Yun Liu, Po-Hsuan Cameron Chen, Shravya Shetty

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

Explaining an increase in predicted risk for clinical alerts.

Michaela Hardt, Alvin Rajkomar, Gerardo Flores, Andrew M. Dai, Michael D. Howell, Greg Corrado, Claire Cui, Moritz Hardt

Proceedings of the ACM CHIL '20: ACM Conference on Health, 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

Publisher Correction: Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer.

Kunal Nagpal, Davis Foote, Yun Liu, Po-Hsuan Cameron Chen, Ellery Wulczyn, Fraser Tan, Niels Olson, Jenny L. Smith, Arash Mohtashamian, James H. Wren, Gregory S. Corrado, Robert MacDonald, Lily H. Peng, Mahul B. Amin, Andrew J. Evans, Ankur R. Sangoi, Craig H. Mermel, Jason D. Hipp, Martin C. Stumpe

npj Digit. Medicine, 2019

Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer.

Kunal Nagpal, Davis Foote, Yun Liu, Po-Hsuan Cameron Chen, Ellery Wulczyn, Fraser Tan, Niels Olson, Jenny L. Smith, Arash Mohtashamian, James H. Wren, Gregory S. Corrado, Robert MacDonald, Lily H. Peng, Mahul B. Amin, Andrew J. Evans, Ankur R. Sangoi, Craig H. Mermel, Jason D. Hipp, Martin C. Stumpe

npj Digit. Medicine, 2019

Similar image search for histopathology: SMILY.

Narayan Hegde, Jason D. Hipp, Yun Liu, Michael Emmert-Buck, Emily Reif, Daniel Smilkov, Michael Terry, Carrie J. Cai, Mahul B. Amin, Craig H. Mermel, Philip Q. Nelson, Lily H. Peng, Gregory S. Corrado, Martin C. Stumpe

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

The Algorithmic Automation Problem: Prediction, Triage, and Human Effort.

Maithra Raghu, Katy Blumer, Greg Corrado, Jon M. Kleinberg, Ziad Obermeyer, Sendhil Mullainathan

CoRR, 2019

TensorFlow.js: Machine Learning For The Web and Beyond.

Daniel Smilkov, Nikhil Thorat, Yannick Assogba, Ann Yuan, Nick Kreeger, Ping Yu, Kangyi Zhang, Shanqing Cai, Eric Nielsen, David Soergel, Stan Bileschi, Michael Terry, Charles Nicholson, Sandeep N. Gupta, Sarah Sirajuddin, D. Sculley, Rajat Monga, Greg Corrado, Fernanda B. Viégas, Martin Wattenberg

Proceedings of the Second Conference on Machine Learning and Systems, SysML 2019, 2019

Human-Centered Tools for Coping with Imperfect Algorithms During Medical Decision-Making.

Carrie J. Cai, Emily Reif, Narayan Hegde, Jason D. Hipp, Been Kim, Daniel Smilkov, Martin Wattenberg, Fernanda B. Viégas, Gregory S. Corrado, Martin C. Stumpe, Michael Terry

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

2018

Scalable and accurate deep learning with electronic health records.

Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Michaela Hardt, Peter J. Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Yi Zhang, Gerardo Flores, Gavin E. Duggan, Jamie Irvine, Quoc Le, Kurt Litsch, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Gregory S. Corrado, Jeffrey Dean

npj Digit. Medicine, 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

Microscope 2.0: An Augmented Reality Microscope with Real-time Artificial Intelligence Integration.

Po-Hsuan Cameron Chen, Krishna Gadepalli, Robert MacDonald, Yun Liu, Kunal Nagpal, Timo Kohlberger, Jeffrey Dean, Gregory S. Corrado, Jason D. Hipp, Martin C. Stumpe

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

Scalable and accurate deep learning for electronic health records.

Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Peter J. Liu, Xiaobing Liu, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Gavin E. Duggan, Gerardo Flores, Michaela Hardt, Jamie Irvine, Quoc V. Le, Kurt Litsch, Jake Marcus, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Greg Corrado, Jeff Dean

CoRR, 2018

2017

Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation.

Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda B. Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, Jeffrey Dean

Trans. Assoc. Comput. Linguistics, 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

Detecting Cancer Metastases on Gigapixel Pathology Images.

Yun Liu, Krishna Gadepalli, Mohammad Norouzi, George E. Dahl, Timo Kohlberger, Aleksey Boyko, Subhashini Venugopalan, Aleksei Timofeev, Philip Q. Nelson, Gregory S. Corrado, Jason D. Hipp, Lily Peng, Martin C. Stumpe

CoRR, 2017

2016

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Lukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, Jeffrey Dean

CoRR, 2016

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Gregory S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian J. Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Józefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Gordon Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul A. Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda B. Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

CoRR, 2016

Wide & Deep Learning for Recommender Systems.

Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil, Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing Liu, Hemal Shah

Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, 2016

Smart Reply: Automated Response Suggestion for Email.

Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufmann, Andrew Tomkins, Balint Miklos, Greg Corrado, László Lukács, Marina Ganea, Peter Young, Vivek Ramavajjala

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015

BilBOWA: Fast Bilingual Distributed Representations without Word Alignments.

Stephan Gouws, Yoshua Bengio, Greg Corrado

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Zero-Shot Learning by Convex Combination of Semantic Embeddings.

Mohammad Norouzi, Tomás Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg Corrado, Jeffrey Dean

Proceedings of the 2nd International Conference on Learning Representations, 2014

2013

Nanoscale electronic synapses using phase change devices.

Bryan L. Jackson, Bipin Rajendran, Gregory S. Corrado, Matthew J. Breitwisch, Geoffrey W. Burr, Roger Cheek, Kailash Gopalakrishnan, Simone Raoux, Charles T. Rettner, Alvaro Padilla, Alejandro G. Schrott, Rohit S. Shenoy, Bülent N. Kurdi, Chung Hon Lam, Dharmendra S. Modha

ACM J. Emerg. Technol. Comput. Syst., 2013

Efficient Estimation of Word Representations in Vector Space

Tomás Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean

Proceedings of the 1st International Conference on Learning Representations, 2013

Distributed Representations of Words and Phrases and their Compositionality.

Tomás Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, Jeffrey Dean

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

DeViSE: A Deep Visual-Semantic Embedding Model.

Andrea Frome, Gregory S. Corrado, Jonathon Shlens, Samy Bengio, Jeffrey Dean, Marc'Aurelio Ranzato, Tomás Mikolov

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Large Scale Distributed Deep Networks.

Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V. Le, Mark Z. Mao, Marc'Aurelio Ranzato, Andrew W. Senior, Paul A. Tucker, Ke Yang, Andrew Y. Ng

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Building high-level features using large scale unsupervised learning.

Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Jeffrey Dean, Andrew Y. Ng

Proceedings of the 29th International Conference on Machine Learning, 2012

Three Controversial Hypotheses Concerning Computation in the Primate Cortex.

Thomas L. Dean, Greg Corrado, Jonathon Shlens

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2009

Recursive Sparse, Spatiotemporal Coding.

Thomas L. Dean, Richard Washington, Greg Corrado

Proceedings of the 11th IEEE International Symposium on Multimedia, 2009