Large-scale analysis of disease pathways in the human interactome. - Monica Agrawal; Marinka Zitnik; Jure Leskovec (PSB, 2018)

Modeling polypharmacy side effects with graph convolutional networks. - Marinka Zitnik; Monica Agrawal; Jure Leskovec (Bioinform., 2018)

TIFTI: A Framework for Extracting Drug Intervals from Longitudinal Clinic Notes. - Monica Agrawal; Griffin Adams; Nathan Nussbaum; Benjamin Birnbaum (CoRR, 2018)

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)

Robust Benchmarking for Machine Learning of Clinical Entity Extraction. - Monica Agrawal; Chloe O'Connell; Yasmin Fatemi; Ariel Levy; David A. Sontag (MLHC, 2020)

Fast, Structured Clinical Documentation via Contextual Autocomplete. - Divya Gopinath; Monica Agrawal; Luke S. Murray; Steven Horng; David R. Karger; David A. Sontag (MLHC, 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 (PSB, 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)

PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming. - Alexander K. Lew; Monica Agrawal; David A. Sontag; Vikash Mansinghka 001 (AISTATS, 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 (CHI, 2021)

Directing Human Attention in Event Localization for Clinical Timeline Creation. - Jason Zhao; Monica Agrawal; Pedram Razavi; David A. Sontag (MLHC, 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 (UIST, 2021)

Leveraging Time Irreversibility with Order-Contrastive Pre-training. - Monica N. Agrawal; Hunter Lang; Michael Offin; Lior Gazit; David A. Sontag (AISTATS, 2022)

Large language models are few-shot clinical information extractors. - Monica Agrawal; Stefan Hegselmann; Hunter Lang; Yoon Kim; David A. Sontag (EMNLP, 2022)

Co-training Improves Prompt-based Learning for Large Language Models. - Hunter Lang; Monica N. Agrawal; Yoon Kim; David A. Sontag (ICML, 2022)

Machine Learning for Health (ML4H) 2022. - Antonio Parziale; Monica Agrawal; Shengpu Tang; Kristen Severson 001; Luis Oala; Adarsh Subbaswamy; Sayantan Kumar; Elora D. M. Schörverth; Stefan Hegselmann; Helen Zhou; Ghada Zamzmi; Purity Mugambi; et al. (ML4H@NeurIPS, 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 symposium 2022 - Extended Abstract track. - Antonio Parziale; Monica Agrawal; Shalmali Joshi; Irene Y. Chen; Shengpu Tang; Luis Oala; Adarsh Subbaswamy (CoRR, 2022)

TabLLM: Few-shot Classification of Tabular Data with Large Language Models. - Stefan Hegselmann; Alejandro Buendia; Hunter Lang; Monica Agrawal; Xiaoyi Jiang 001; David A. Sontag (AISTATS, 2023)

Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes. - Sharon Jiang; Shannon Shen 001; Monica Agrawal; Barbara D. Lam; Nicholas Kurtzman; Steven Horng; David R. Karger; David A. Sontag (MLHC, 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; et al. (CoRR, 2023)

Towards Scalable Structured Data from Clinical Text - Monica Agrawal (2023)

A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models. - Stefan Hegselmann; Shannon Shen 001; Florian Gierse; Monica Agrawal; David A. Sontag; Xiaoyi Jiang 001 (CHIL, 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; et al. (CoRR, 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 003; Rahul Thapa; Hussein Mozannar; William Jongwon Han; Nikita Mehandru; Michael Wornow; Vladislav Lialin; Xin Liu 034; Alejandro Lozano; Jiacheng Zhu; et al. (CoRR, 2024)

Generative AI in Medicine. - Divya Shanmugam; Monica Agrawal; Rajiv Movva; Irene Y. Chen; Marzyeh Ghassemi; Maia Jacobs; Emma Pierson (CoRR, 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 001; Nicholas Kurtzman; Steven Horng; David R. Karger; David A. Sontag (J. Am. Medical Informatics Assoc., 2024)

How does my language model understand clinical text? - Furong Jia 002; David A. Sontag; Monica Agrawal (CHIL, 2025)

Application of unified health large language model evaluation framework to In-Basket message replies: bridging qualitative and quantitative assessments. - Chuan Hong; Anand Chowdhury; Anthony D. Sorrentino; Haoyuan Wang; Monica Agrawal; Armando Bedoya; Sophia Bessias; Nicoleta J. Economou-Zavlanos; Ian Wong; Christian Pean; Fan Li; Kathryn I. Pollak; et al. (J. Am. Medical Informatics Assoc., 2025)

An evaluation framework for ambient digital scribing tools in clinical applications. - Haoyuan Wang; Rui Yang; Mahmoud Alwakeel; Ankit Kayastha; Anand Chowdhury; Joshua M. Biro; Anthony D. Sorrentino; Jessica L. Handley; Sarah Hantzmon; Sophia Bessias; Nicoleta J. Economou-Zavlanos; Armando Bedoya; et al. (npj Digit. Medicine, 2025)

Retrieval-augmented systems can be dangerous medical communicators. - Lionel Wong; Ayman Ali; Raymond Xiong; Shannon Zejiang Shen; Yoon Kim; Monica Agrawal (CoRR, 2025)

Diagnosing our datasets: How does my language model learn clinical information? - Furong Jia 002; David A. Sontag; Monica Agrawal (CoRR, 2025)

"What's Up, Doc?": Analyzing How Users Seek Health Information in Large-Scale Conversational AI Datasets. - Akshay Paruchuri; Maryam Aziz; Rohit Vartak; Ayman Ali; Best Uchehara; Xin Liu 034; Ishan Chatterjee; Monica Agrawal (CoRR, 2025)