Alvin Rajkomar

According to our database, Alvin Rajkomar authored at least 10 papers between 2017 and 2023.

Collaborative distances:

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

2023

SDOH-NLI: a Dataset for Inferring Social Determinants of Health from Clinical Notes.

Ádám D. Lelkes, Eric Loreaux, Tal Schuster, Ming-Jun Chen, Alvin Rajkomar

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 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

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

Modelling EHR timeseries by restricting feature interaction.

Kun Zhang, Yuan Xue, Gerardo Flores, Alvin Rajkomar, Claire Cui, Andrew M. Dai

CoRR, 2019

Improved Patient Classification with Language Model Pretraining Over Clinical Notes.

Jonas Kemp, Alvin Rajkomar, Andrew M. Dai

CoRR, 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

Reply: metrics to assess machine learning models.

Alvin Rajkomar, Andrew M. Dai, Mimi Sun, Michaela Hardt, Kai Chen, Kathryn Rough, Jeffrey Dean

npj Digit. Medicine, 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

Semi-supervised Learning for Information Extraction from Dialogue.

Anjuli Kannan, Kai Chen, Diana Jaunzeikare, Alvin Rajkomar

Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018

2017

High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks.

Alvin Rajkomar, Sneha Lingam, Andrew G. Taylor, Michael Blum, John Mongan

J. Digit. Imaging, 2017