Monica Agrawal

According to our database, Monica Agrawal authored at least 26 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing.

Sharon Jiang, Barbara D. Lam, Monica Agrawal, Shannon Shen, Nicholas Kurtzman, Steven Horng, David R. Karger, David A. Sontag

J. Am. Medical Informatics Assoc., 2024

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.

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

CoRR, 2024

A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models.

Stefan Hegselmann, Shannon Zejiang Shen, Florian Gierse, Monica Agrawal, David A. Sontag, Xiaoyi Jiang

CoRR, 2024

Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study.

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

CoRR, 2024

2023

Towards Scalable Structured Data from Clinical Text

Monica Agrawal

PhD thesis, 2023

Use large language models to promote equity.

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

CoRR, 2023

Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes.

Sharon Jiang, Shannon Shen, Monica Agrawal, Barbara D. Lam, Nicholas Kurtzman, Steven Horng, David R. Karger, David A. Sontag

Proceedings of the Machine Learning for Healthcare Conference, 2023

TabLLM: Few-shot Classification of Tabular Data with Large Language Models.

Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David A. Sontag

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Machine Learning for Health symposium 2022 - Extended Abstract track.

Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy

CoRR, 2022

Large Language Models are Zero-Shot Clinical Information Extractors.

Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David A. Sontag

CoRR, 2022

Machine Learning for Health (ML4H) 2022.

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

Proceedings of the Machine Learning for Health, 2022

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

Hunter Lang, Monica N. Agrawal, Yoon Kim, David A. Sontag

Proceedings of the International Conference on Machine Learning, 2022

Large language models are few-shot clinical information extractors.

Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David A. Sontag

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Leveraging Time Irreversibility with Order-Contrastive Pre-training.

Monica N. Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David A. Sontag

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records.

Luke S. Murray, Divya Gopinath, Monica Agrawal, Steven Horng, David A. Sontag, David R. Karger

Proceedings of the UIST '21: The 34th Annual ACM Symposium on User Interface Software and Technology, 2021

Directing Human Attention in Event Localization for Clinical Timeline Creation.

Jason Zhao, Monica Agrawal, Pedram Razavi, David A. Sontag

Proceedings of the Machine Learning for Healthcare Conference, 2021

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 A. Sontag

Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

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

Alexander K. Lew, Monica Agrawal, David A. Sontag, Vikash Mansinghka

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

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

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

CoRR, 2020

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

Irene Y. Chen, Monica Agrawal, Steven Horng, David A. Sontag

Proceedings of the Pacific Symposium on Biocomputing 2020, 2020

Fast, Structured Clinical Documentation via Contextual Autocomplete.

Divya Gopinath, Monica Agrawal, Luke S. Murray, Steven Horng, David R. Karger, David A. Sontag

Proceedings of the Machine Learning for Healthcare Conference, 2020

Robust Benchmarking for Machine Learning of Clinical Entity Extraction.

Monica Agrawal, Chloe O'Connell, Yasmin Fatemi, Ariel Levy, David A. Sontag

Proceedings of the Machine Learning for Healthcare Conference, 2020

2019

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

Irene Y. Chen, Monica Agrawal, Steven Horng, David A. Sontag

CoRR, 2019

2018

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

Monica Agrawal, Griffin Adams, Nathan Nussbaum, Benjamin Birnbaum

CoRR, 2018

Modeling polypharmacy side effects with graph convolutional networks.

Marinka Zitnik, Monica Agrawal, Jure Leskovec

Bioinform., 2018

Large-scale analysis of disease pathways in the human interactome.

Monica Agrawal, Marinka Zitnik, Jure Leskovec

Proceedings of the Biocomputing 2018: Proceedings of the Pacific Symposium, 2018