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Trove: Ontology-driven weak supervision for medical entity classification


Aug 05, 2020
Jason A. Fries, Ethan Steinberg, Saelig Khattar, Scott L. Fleming, Jose Posada, Alison Callahan, Nigam H. Shah


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An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction


Jul 20, 2020
Stephen R. Pfohl, Agata Foryciarz, Nigam H. Shah


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Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data


Jan 06, 2020
Ethan Steinberg, Ken Jung, Jason A. Fries, Conor K. Corbin, Stephen R. Pfohl, Nigam H. Shah


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Counterfactual Reasoning for Fair Clinical Risk Prediction


Jul 14, 2019
Stephen Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah

* Machine Learning for Healthcare 2019 

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A Semi-Supervised Machine Learning Approach to Detecting Recurrent Metastatic Breast Cancer Cases Using Linked Cancer Registry and Electronic Medical Record Data


Jan 17, 2019
Albee Y. Ling, Allison W. Kurian, Jennifer L. Caswell-Jin, George W. Sledge Jr., Nigam H. Shah, Suzanne R. Tamang


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Predicting Inpatient Discharge Prioritization With Electronic Health Records


Dec 02, 2018
Anand Avati, Stephen Pfohl, Chris Lin, Thao Nguyen, Meng Zhang, Philip Hwang, Jessica Wetstone, Kenneth Jung, Andrew Ng, Nigam H. Shah


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The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data


Oct 04, 2018
Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah

* Pacific Symposium on Biocomputing (PSB) 2019, Hawaii, https://psb.stanford.edu/psb-online/; 13 pages, 7 figures; updated with the camera-ready version of the manuscript 

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Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk


Sep 16, 2018
Stephen Pfohl, Ben Marafino, Adrien Coulet, Fatima Rodriguez, Latha Palaniappan, Nigam H. Shah


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Countdown Regression: Sharp and Calibrated Survival Predictions


Jun 21, 2018
Anand Avati, Tony Duan, Kenneth Jung, Nigam H. Shah, Andrew Ng


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Scalable and accurate deep learning for electronic health records


May 11, 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 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

* npj Digital Medicine 1:18 (2018) 
* Published version from https://www.nature.com/articles/s41746-018-0029-1 

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Improving Palliative Care with Deep Learning


Nov 17, 2017
Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Ng, Nigam H. Shah

* IEEE International Conference on Bioinformatics and Biomedicine 2017 

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Some methods for heterogeneous treatment effect estimation in high-dimensions


Jul 01, 2017
Scott Powers, Junyang Qian, Kenneth Jung, Alejandro Schuler, Nigam H. Shah, Trevor Hastie, Robert Tibshirani


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