Monica Agrawal
Monica Agrawal
Incoming Assistant Professor, Duke
Verified email at - Homepage
Cited by
Cited by
Modeling polypharmacy side effects with graph convolutional networks
M Zitnik, M Agrawal, J Leskovec
Bioinformatics 34 (13), i457-i466, 2018
Large language models are few-shot clinical information extractors
M Agrawal, S Hegselmann, H Lang, Y Kim, D Sontag
Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022
Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research
B Birnbaum, N Nussbaum, K Seidl-Rathkopf, M Agrawal, M Estevez, ...
arXiv preprint arXiv:2001.09765, 2020
Large-scale analysis of disease pathways in the human interactome
M Agrawal, M Zitnik, J Leskovec
PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018: Proceedings of the Pacific Symposium …, 2018
TabLLM: few-shot classification of tabular data with large language models
S Hegselmann, A Buendia, H Lang, M Agrawal, X Jiang, D Sontag
International Conference on Artificial Intelligence and Statistics, 5549-5581, 2023
Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative
A Levy, M Agrawal, A Satyanarayan, D Sontag
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021
Systems and methods for model-assisted cohort selection
BE Birnbaum, JD Haimson, LDK He, KN Seidl-Rathkopf, MN Agrawal, ...
US Patent 10,304,000, 2019
Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph
IY Chen, M Agrawal, S Horng, D Sontag
Pac Symp Biocomput, 19-30, 2020
Co-training improves prompt-based learning for large language models
H Lang, MN Agrawal, Y Kim, D Sontag
International Conference on Machine Learning, 11985-12003, 2022
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming
A Lew, M Agrawal, D Sontag, V Mansinghka
International Conference on Artificial Intelligence and Statistics, 1927-1935, 2021
Fast, Structured Clinical Documentation via Contextual Autocomplete
D Gopinath, M Agrawal, L Murray, S Horng, D Karger, D Sontag
Machine Learning for Healthcare Conference, 842-870, 2020
Single-shot speckle noise reduction by interleaved optical coherence tomography
L Duan, HY Lee, G Lee, M Agrawal, GT Smith, AK Ellerbee
Journal of Biomedical Optics 19 (12), 120501, 2014
MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records
L Murray, D Gopinath, M Agrawal, S Horng, D Sontag, DR Karger
The 34th Annual ACM Symposium on User Interface Software and Technology …, 2021
Fabrication of healthy and disease-mimicking retinal phantoms with tapered foveal pits for optical coherence tomography
GCF Lee, GT Smith, M Agrawal, T Leng, AK Ellerbee
Journal of biomedical optics 20 (8), 085004, 2015
Leveraging Time Irreversibility with Order-Contrastive Pre-training
MN Agrawal, H Lang, M Offin, L Gazit, D Sontag
International Conference on Artificial Intelligence and Statistics, 2330-2353, 2022
Directing Human Attention in Event Localization for Clinical Timeline Creation
J Zhao, M Agrawal, P Razavi, D Sontag
Machine Learning for Healthcare Conference, 80-102, 2021
What’s up, doc? a medical diagnosis bot
M Agrawal, J Cheng, C Tran
Spoken Language Processing (CS224S), Spring 2017, 2017
Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer
MS Alkaitis, MN Agrawal, GJ Riely, P Razavi, D Sontag
JCO Clinical Cancer Informatics 5, 550-560, 2021
TIFTI: A Framework for Extracting Drug Intervals from Longitudinal Clinic Notes
M Agrawal, G Adams, N Nussbaum, B Birnbaum
arXiv preprint arXiv:1811.12793, 2018
Robust Benchmarking for Machine Learning of Clinical Entity Extraction
M Agrawal, C O’Connell, Y Fatemi, A Levy, D Sontag
Machine Learning for Healthcare Conference, 928-949, 2020
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