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2020 – today
- 2024
[j2]Sharon Jiang
, Barbara D. Lam, Monica Agrawal, Shannon Shen, Nicholas Kurtzman, Steven Horng, David R. Karger, David A. Sontag:
Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing. J. Am. Medical Informatics Assoc. 31(7): 1578-1582 (2024)- [i20]Niklas Mannhardt, Elizabeth Bondi-Kelly, Barbara D. Lam, Chloe O'Connell, Mercy Asiedu, Hussein Mozannar, Monica Agrawal, Alejandro Buendia, Tatiana Urman, Irbaz B. Riaz, Catherine E. Ricciardi, Marzyeh Ghassemi, David A. Sontag:
Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study. CoRR abs/2401.09637 (2024) - [i19]Stefan Hegselmann, Shannon Zejiang Shen, Florian Gierse, Monica Agrawal, David A. Sontag, Xiaoyi Jiang:
A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models. CoRR abs/2402.15422 (2024) - [i18]Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo:
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR abs/2403.01628 (2024) - 2023
- [b1]Monica Agrawal:
Towards Scalable Structured Data from Clinical Text. MIT, USA, 2023 - [c14]Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David A. Sontag:
TabLLM: Few-shot Classification of Tabular Data with Large Language Models. AISTATS 2023: 5549-5581 - [c13]Sharon Jiang, Shannon Shen, Monica Agrawal, Barbara D. Lam, Nicholas Kurtzman, Steven Horng, David R. Karger, David A. Sontag:
Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes. MLHC 2023: 343-359 - [i17]Sharon Jiang, Shannon Shen, Monica Agrawal, Barbara D. Lam, Nicholas Kurtzman, Steven Horng, David R. Karger, David A. Sontag:
Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes. CoRR abs/2308.08494 (2023) - [i16]Emma Pierson, Divya Shanmugam, Rajiv Movva, Jon M. Kleinberg, Monica Agrawal, Mark Dredze, Kadija Ferryman, Judy Wawira Gichoya, Dan Jurafsky, Pang Wei Koh, Karen Levy, Sendhil Mullainathan, Ziad Obermeyer, Harini Suresh, Keyon Vafa:
Use large language models to promote equity. CoRR abs/2312.14804 (2023) - 2022
- [c12]Monica N. Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David A. Sontag:
Leveraging Time Irreversibility with Order-Contrastive Pre-training. AISTATS 2022: 2330-2353 - [c11]Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David A. Sontag:
Large language models are few-shot clinical information extractors. EMNLP 2022: 1998-2022 - [c10]Hunter Lang, Monica N. Agrawal, Yoon Kim, David A. Sontag:
Co-training Improves Prompt-based Learning for Large Language Models. ICML 2022: 11985-12003 - [c9]Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed M. Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi:
Machine Learning for Health (ML4H) 2022. ML4H@NeurIPS 2022: 1-11 - [e1]Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy:
Machine Learning for Health, ML4H 2022, 28 November 2022, New Orleans, Lousiana, USA & Virtual. Proceedings of Machine Learning Research 193, PMLR 2022 [contents] - [i15]Hunter Lang, Monica Agrawal, Yoon Kim, David A. Sontag:
Co-training Improves Prompt-based Learning for Large Language Models. CoRR abs/2202.00828 (2022) - [i14]Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David A. Sontag:
Large Language Models are Zero-Shot Clinical Information Extractors. CoRR abs/2205.12689 (2022) - [i13]Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David A. Sontag:
TabLLM: Few-shot Classification of Tabular Data with Large Language Models. CoRR abs/2210.10723 (2022) - [i12]Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy:
Machine Learning for Health symposium 2022 - Extended Abstract track. CoRR abs/2211.15564 (2022) - 2021
- [c8]Alexander K. Lew, Monica Agrawal, David A. Sontag, Vikash Mansinghka:
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming. AISTATS 2021: 1927-1935 - [c7]Ariel Levy, Monica Agrawal, Arvind Satyanarayan, David A. Sontag:
Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative. CHI 2021: 72:1-72:13 - [c6]Jason Zhao, Monica Agrawal, Pedram Razavi, David A. Sontag:
Directing Human Attention in Event Localization for Clinical Timeline Creation. MLHC 2021: 80-102 - [c5]Luke S. Murray, Divya Gopinath, Monica Agrawal, Steven Horng, David A. Sontag, David R. Karger:
MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records. UIST 2021: 1169-1183 - [i11]Ariel Levy, Monica Agrawal, Arvind Satyanarayan, David A. Sontag:
Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative. CoRR abs/2103.04725 (2021) - [i10]Luke S. Murray, Divya Gopinath, Monica Agrawal, Steven Horng, David A. Sontag, David R. Karger:
MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records. CoRR abs/2109.11451 (2021) - [i9]Monica Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David A. Sontag:
Leveraging Time Irreversibility with Order-Contrastive Pre-training. CoRR abs/2111.02599 (2021) - 2020
- [c4]Divya Gopinath, Monica Agrawal, Luke S. Murray, Steven Horng, David R. Karger, David A. Sontag:
Fast, Structured Clinical Documentation via Contextual Autocomplete. MLHC 2020: 842-870 - [c3]Monica Agrawal, Chloe O'Connell, Yasmin Fatemi, Ariel Levy, David A. Sontag:
Robust Benchmarking for Machine Learning of Clinical Entity Extraction. MLHC 2020: 928-949 - [c2]Irene Y. Chen, Monica Agrawal, Steven Horng, David A. Sontag:
Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health KnowledgeGraph. PSB 2020: 19-30 - [i8]Benjamin Birnbaum, Nathan Nussbaum, Katharina Seidl-Rathkopf, Monica Agrawal, Melissa Estevez, Evan Estola, Joshua Haimson, Lucy He, Peter Larson, Paul Richardson:
Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research. CoRR abs/2001.09765 (2020) - [i7]Alexander K. Lew, Monica Agrawal, David A. Sontag, Vikash K. Mansinghka:
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming. CoRR abs/2007.11838 (2020) - [i6]Divya Gopinath, Monica Agrawal, Luke S. Murray, Steven Horng, David R. Karger, David A. Sontag:
Fast, Structured Clinical Documentation via Contextual Autocomplete. CoRR abs/2007.15153 (2020) - [i5]Monica Agrawal, Chloe O'Connell, Yasmin Fatemi, Ariel Levy, David A. Sontag:
Robust Benchmarking for Machine Learning of Clinical Entity Extraction. CoRR abs/2007.16127 (2020)
2010 – 2019
- 2019
- [i4]Irene Y. Chen, Monica Agrawal, Steven Horng, David A. Sontag:
Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph. CoRR abs/1910.01116 (2019) - 2018
- [j1]Marinka Zitnik, Monica Agrawal, Jure Leskovec:
Modeling polypharmacy side effects with graph convolutional networks. Bioinform. 34(13): i457-i466 (2018) - [c1]Monica Agrawal, Marinka Zitnik, Jure Leskovec:
Large-scale analysis of disease pathways in the human interactome. PSB 2018: 111-122 - [i3]Marinka Zitnik, Monica Agrawal, Jure Leskovec:
Modeling polypharmacy side effects with graph convolutional networks. CoRR abs/1802.00543 (2018) - [i2]Monica Agrawal, Griffin Adams, Nathan Nussbaum, Benjamin Birnbaum:
TIFTI: A Framework for Extracting Drug Intervals from Longitudinal Clinic Notes. CoRR abs/1811.12793 (2018) - 2017
- [i1]Monica Agrawal, Marinka Zitnik, Jure Leskovec:
Large-scale analysis of disease pathways in the human interactome. CoRR abs/1712.00843 (2017)
Coauthor Index
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