Alvin Rajkomar

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 12

Top Topics

Electronic Health Records

Microarray Gene

Language Models For Information Retrieval

Top Venues

npj Digit. Medicine

Publications

Ádám D. Lelkes, Eric Loreaux, Tal Schuster, Ming-Jun Chen, Alvin Rajkomar
SDOH-NLI: a Dataset for Inferring Social Determinants of Health from Clinical Notes. EMNLP (Findings) (2023)
Ádám D. Lelkes, Eric Loreaux, Tal Schuster, Ming-Jun Chen, Alvin Rajkomar
SDOH-NLI: a Dataset for Inferring Social Determinants of Health from Clinical Notes. CoRR (2023)
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
Large Language Models Encode Clinical Knowledge. CoRR (2022)
Michaela Hardt, Alvin Rajkomar, Gerardo Flores, Andrew M. Dai, Michael Howell, Greg Corrado, Claire Cui, Moritz Hardt
Explaining an increase in predicted risk for clinical alerts. CHIL (2020)
Michaela Hardt, Alvin Rajkomar, Gerardo Flores, Andrew M. Dai, Michael Howell, Greg Corrado, Claire Cui, Moritz Hardt
Explaining an increase in predicted risk for clinical alerts. CoRR (2019)
Jonas Kemp, Alvin Rajkomar, Andrew M. Dai
Improved Patient Classification with Language Model Pretraining Over Clinical Notes. CoRR (2019)
Kun Zhang, Yuan Xue, Gerardo Flores, Alvin Rajkomar, Claire Cui, Andrew M. Dai
Modelling EHR timeseries by restricting feature interaction. CoRR (2019)
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
Scalable and accurate deep learning with electronic health records. npj Digit. Medicine 1 (2018)
Anjuli Kannan, Kai Chen, Diana Jaunzeikare, Alvin Rajkomar
Semi-supervised Learning for Information Extraction from Dialogue. INTERSPEECH (2018)
Alvin Rajkomar, Andrew M. Dai, Mimi Sun, Michaela Hardt, Kai Chen, Kathryn Rough, Jeffrey Dean
Reply: metrics to assess machine learning models. npj Digit. Medicine 1 (2018)
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 Howell, Claire Cui, Greg Corrado, Jeff Dean
Scalable and accurate deep learning for electronic health records. CoRR (2018)
Alvin Rajkomar, Sneha Lingam, Andrew G. Taylor, Michael Blum, John Mongan
High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks. J. Digit. Imaging 30 (1) (2017)