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2020 – today
- 2023
[c3]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: 4789-4798- [i6]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 abs/2310.18431 (2023) - 2022
- [i5]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 abs/2212.13138 (2022) - 2020
- [c2]Michaela Hardt, Alvin Rajkomar, Gerardo Flores, Andrew M. Dai, Michael D. Howell, Greg Corrado, Claire Cui, Moritz Hardt:
Explaining an increase in predicted risk for clinical alerts. CHIL 2020: 80-89
2010 – 2019
- 2019
- [i4]Michaela Hardt, Alvin Rajkomar, Gerardo Flores, Andrew M. Dai, Michael D. Howell, Greg Corrado, Claire Cui, Moritz Hardt:
Explaining an increase in predicted risk for clinical alerts. CoRR abs/1907.04911 (2019) - [i3]Jonas Kemp, Alvin Rajkomar, Andrew M. Dai:
Improved Patient Classification with Language Model Pretraining Over Clinical Notes. CoRR abs/1909.03039 (2019) - [i2]Kun Zhang, Yuan Xue, Gerardo Flores, Alvin Rajkomar, Claire Cui, Andrew M. Dai:
Modelling EHR timeseries by restricting feature interaction. CoRR abs/1911.06410 (2019) - 2018
- [j3]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) - [j2]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) - [c1]Anjuli Kannan, Kai Chen, Diana Jaunzeikare, Alvin Rajkomar:
Semi-supervised Learning for Information Extraction from Dialogue. INTERSPEECH 2018: 2077-2081 - [i1]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:
Scalable and accurate deep learning for electronic health records. CoRR abs/1801.07860 (2018) - 2017
- [j1]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): 95-101 (2017)
Coauthor Index
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