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2020 – today
- 2024
[i14]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:
HeAR - Health Acoustic Representations. CoRR abs/2403.02522 (2024)- 2023
- [i13]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:
Predicting Cardiovascular Disease Risk using Photoplethysmography and Deep Learning. CoRR abs/2305.05648 (2023) - [i12]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:
ELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders. CoRR abs/2308.01317 (2023) - 2022
- [j1]Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley:
Underspecification Presents Challenges for Credibility in Modern Machine Learning. J. Mach. Learn. Res. 23: 226:1-226:61 (2022) - [c3]Subhrajit Roy, Diana Mincu, Lev Proleev, Negar Rostamzadeh, Chintan Ghate, Natalie Harris, Christina Chen, Jessica Schrouff, Nenad Tomasev, Fletcher Lee Hartsell, Katherine A. Heller:
Disability prediction in multiple sclerosis using performance outcome measures and demographic data. CHIL 2022: 375-396 - [c2]Daniel Lopez Martinez, Christina Chen, Ming-Jun Chen:
Machine Learning for Dynamically Predicting the Onset of Renal Replacement Therapy in Chronic Kidney Disease Patients Using Claims Data. AMAI@MICCAI 2022: 18-28 - [c1]Jessica Schrouff, Natalie Harris, Sanmi Koyejo, Ibrahim M. Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour:
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. NeurIPS 2022 - [i11]Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour:
Maintaining fairness across distribution shift: do we have viable solutions for real-world applications? CoRR abs/2202.01034 (2022) - [i10]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:
AI system for fetal ultrasound in low-resource settings. CoRR abs/2203.10139 (2022) - [i9]Chace Lee, Angelica Willis, Christina Chen, Marcin Sieniek, Akib Uddin, Jonny Wong, Rory Pilgrim, Katherine Chou, Daniel Tse, Shravya Shetty, Ryan G. Gomes:
Enabling faster and more reliable sonographic assessment of gestational age through machine learning. CoRR abs/2203.11903 (2022) - [i8]Subhrajit Roy, Diana Mincu, Lev Proleev, Negar Rostamzadeh, Chintan Ghate, Natalie Harris, Christina Chen, Jessica Schrouff, Nenad Tomasev, Fletcher Lee Hartsell, Katherine A. Heller:
Disability prediction in multiple sclerosis using performance outcome measures and demographic data. CoRR abs/2204.03969 (2022) - [i7]Eric Loreaux, Ke Yu, Jonas Kemp, Martin Seneviratne, Christina Chen, Subhrajit Roy, Ivan Protsyuk, Natalie Harris, Alexander D'Amour, Steve Yadlowsky, Mingjun Chen:
Boosting the interpretability of clinical risk scores with intervention predictions. CoRR abs/2207.02941 (2022) - [i6]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:
Discovering novel systemic biomarkers in photos of the external eye. CoRR abs/2207.08998 (2022) - [i5]Daniel Lopez Martinez, Christina Chen, Mingjun Chen:
Machine learning for dynamically predicting the onset of renal replacement therapy in chronic kidney disease patients using claims data. CoRR abs/2209.01469 (2022) - 2021
- [i4]Gloria Hyun-Jung Kwak, Christina Chen, Lowell Ling, Erina Ghosh, Leo Anthony Celi, Pan Hui:
Predicting Hyperkalemia in the ICU and Evaluation of Generalizability and Interpretability. CoRR abs/2101.06443 (2021) - [i3]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:
Deep learning for detecting pulmonary tuberculosis via chest radiography: an international study across 10 countries. CoRR abs/2105.07540 (2021) - [i2]Jeya Maria Jose Valanarasu, Christina Chen, Vishal M. Patel:
R2D: Learning Shadow Removal to Enhance Fine-Context Shadow Detection. CoRR abs/2109.09609 (2021) - 2020
- [i1]Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley:
Underspecification Presents Challenges for Credibility in Modern Machine Learning. CoRR abs/2011.03395 (2020)
Coauthor Index
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