Publications

An up-to-date list can be found on my Google scholar page.

Papers


Large Language Models are Few-shot Clinical Information Extractors
Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David Sontag
EMNLP, 2022, Oral Presentation.
[Paper] [Press] [Dataset]

Co-training Improves Prompt-based Learning for Large Language Models
Hunter Lang, Monica Agrawal, Yoon Kim, David Sontag
ICML, 2022.
[Paper] [Code]

Leveraging Time Irreversibility with Order-Contrastive Pre-training
Monica Agrawal*, Hunter Lang*, Michael Offin, Lior Gazit, David Sontag
AISTATS, 2022.
[Paper]

MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records
Luke Murray, Divya Gopinath, Monica Agrawal, Steven Horng, David Sontag, David Karger
UIST, 2021.
[Paper] [Website (including Videos + Press)]

Directing Human Attention in Event Localization for Clinical Timeline Creation
Jason Zhao*, Monica Agrawal*, Pedram Razavi, David Sontag
Machine Learning for Healthcare, 2021.
[Paper] [Video]

Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer
Matthew Alkaitis, Monica Agrawal, Gregory Riely, Pedram Razavi, David Sontag
JCO Clinical Cancer Informatics , 2021.
[Paper]

Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative
Ariel Levy*, Monica Agrawal*, Arvind Satyanarayan, David Sontag
CHI, 2021.
[Paper] [Code] [Video]

PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming
Alex Lew, Monica Agrawal, David Sontag, Vikash Mansinghka
AISTATS, 2021, Oral Presentation.
[Paper] [Press] [Code]

Robust benchmarking for machine learning of clinical entity extraction
Monica Agrawal, Chloe O'Connell, Yasmin Fatemi, Ariel Levy, David Sontag
Machine Learning for Healthcare, 2020.
[Paper] [Video]

Fast, structured clinical documentation via contextual autocomplete
Divya Gopinath, Monica Agrawal, Luke Murray, Steven Horng, David Karger, David Sontag
Machine Learning for Healthcare, 2020.
[Paper] [Video]

Robustly extracting medical knowledge from EHRs: A case study of learning a health knowledge graph
Irene Y. Chen, Monica Agrawal, Steven Horng, David Sontag
Pacific Symposium on Biocomputing, 2020.
[Paper] [Press]

Modeling polypharmacy side effects with graph convolutional networks
Marinka Zitnik, Monica Agrawal, Jure Leskovec
Bioinformatics, 2018.
[Paper] [Description] [Press] [Code]

Large-scale analysis of disease pathways in the human interactome.
Monica Agrawal*, Marinka Zitnik*, Jure Leskovec
Pacific Symposium on Biocomputing, 2018.
[Paper] [Description] [Code]

Fabrication of healthy and disease-mimicking retinal phantoms with tapered foveal pits for optical coherence tomography.
Gary Lee, Gennifer Smith, Monica Agrawal, Theodore Lang, Audrey Ellerbee.
Journal of Biomedical Optics, 2015.
[Paper]

Single-shot speckle noise reduction by interleaved optical coherence tomography
Lian Duan, Hee Yoon Lee, Gary Lee, Monica Agrawal, Gennifer Smith, Audrey Ellerbee.
Journal of Biomedical Optics, 2014.
[Paper]

Workshops


PClean: Probabilistic scripts for automating common-sense data cleaning
Alex Lew, Monica Agrawal, Vikash Mansinghka.
NeurIPS KR2ML Workshop, 2019.

TIFTI: A Framework for Extracting Drug Intervals from Longitudinal Clinic Notes
Monica Agrawal, Griffin Adams, Nathan Nussbaum, Benjamin Birnbaum.
NeurIPS ML4H Workshop, 2018.
[Paper]

Patents


Systems and methods for model-assisted cohort selection.
Benjamin Birnbaum, Joshua Haimson, Lucy He, Katharina Seidl-Rathkopf, Monica Agrawal, Nathan Nussbaum.
US Patent App, 2018.
[Description]