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Large Language Models are Zero-Shot Clinical Information Extractors


May 25, 2022
Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David Sontag


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Co-training Improves Prompt-based Learning for Large Language Models


Feb 02, 2022
Hunter Lang, Monica Agrawal, Yoon Kim, David Sontag

* 17 pages, 8 figures 

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Leveraging Time Irreversibility with Order-Contrastive Pre-training


Nov 04, 2021
Monica Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David Sontag


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PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming


Aug 07, 2020
Alexander K. Lew, Monica Agrawal, David Sontag, Vikash K. Mansinghka

* Added references; revised abstract 

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Robust Benchmarking for Machine Learning of Clinical Entity Extraction


Jul 31, 2020
Monica Agrawal, Chloe O'Connell, Yasmin Fatemi, Ariel Levy, David Sontag


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Fast, Structured Clinical Documentation via Contextual Autocomplete


Jul 29, 2020
Divya Gopinath, Monica Agrawal, Luke Murray, Steven Horng, David Karger, David Sontag

* Published in Machine Learning for Healthcare 2020 conference 

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Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research


Jan 13, 2020
Benjamin Birnbaum, Nathan Nussbaum, Katharina Seidl-Rathkopf, Monica Agrawal, Melissa Estevez, Evan Estola, Joshua Haimson, Lucy He, Peter Larson, Paul Richardson

* Word count: Abstract, 254; text, 3934 Keywords: electronic health record; machine learning; cancer; real-world evidence 

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Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph


Oct 02, 2019
Irene Y. Chen, Monica Agrawal, Steven Horng, David Sontag

* 12 pages, presented at PSB 2020 

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TIFTI: A Framework for Extracting Drug Intervals from Longitudinal Clinic Notes


Dec 03, 2018
Monica Agrawal, Griffin Adams, Nathan Nussbaum, Benjamin Birnbaum

* Machine Learning for Health (ML4H) Workshop at NeurIPS 2018 arXiv:1811.07216 

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