Monica Agrawal

54 papers A* 3A 2Misc 2Journal 34Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Batch-of-Thought: Cross-Instance Learning for Enhanced LLM Reasoning. CoRR Xuan Yang, Furong Jia, Roy Xie, Xiong Xi, Hengwei Bian, Jian Li, Monica Agrawal
2026	J	`jnl`	MedRedFlag: Investigating how LLMs Redirect Misconceptions in Real-World Health Communication. CoRR Sraavya Sambara, Yuan Pu, Ayman Ali, Vishala Mishra, Lionel Wong, Monica Agrawal
2026	J	`jnl`	What Patients Really Ask: Exploring the Effect of False Assumptions in Patient Information Seeking. CoRR Raymond M. Xiong, Furong Jia, Lionel Wong, Monica Agrawal
2025	—	`conf`	"What's Up, Doc?": Analyzing How Users Seek Health Information in Large-Scale Conversational AI Datasets. EMNLP (Findings) Akshay Paruchuri, Maryam Aziz, Rohit Vartak, Ayman Ali, Best Uchehara, Xin Liu, Ishan Chatterjee, Monica Agrawal
2025	J	`jnl`	"What's Up, Doc?": Analyzing How Users Seek Health Information in Large-Scale Conversational AI Datasets. CoRR Akshay Paruchuri, Maryam Aziz, Rohit Vartak, Ayman Ali, Best Uchehara, Xin Liu, Ishan Chatterjee, Monica Agrawal
2025	J	`jnl`	An Agentic AI System for Multi-Framework Communication Coding. CoRR Bohao Yang, Rui Yang, Joshua M. Biro, Haoyuan Wang, Jessica L. Handley, Brianna Richardson, Sophia Bessias, Nicoleta J. Economou-Zavlanos, Armando Bedoya, Monica Agrawal, Michael M. Zavlanos, Anand Chowdhury, Raj M. Ratwani, Kai Sun, Kathryn I. Pollak, Michael J. Pencina, Chuan Hong
2025	J	`jnl`	An evaluation framework for ambient digital scribing tools in clinical applications. npj Digit. Medicine 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, Monica Agrawal, Raj M. Ratwani, Eric G. Poon, Michael J. Pencina, Kathryn I. Pollak, Chuan Hong
2025	J	`jnl`	Application of unified health large language model evaluation framework to In-Basket message replies: bridging qualitative and quantitative assessments. J. Am. Medical Informatics Assoc. 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, Eric G. Poon, Michael J. Pencina
2025	—	`ed.`	Conference on Health, Inference, and Learning, UC Berkeley, Berkeley, USA, 25-27 June 2025. CHIL Xuhai Orson Xu, Edward Choi, Pankhuri Singhal, Walter Gerych, Shengpu Tang, Monica Agrawal, Adarsh Subbaswamy, Elena Sizikova, Jessilyn Dunn, Roxana Daneshjou, Tasmie Sarker, Matthew McDermott, Irene Chen
2025	J	`jnl`	Counting Clues: A Lightweight Probabilistic Baseline Can Match an LLM. CoRR Furong Jia, Yuan Pu, Finn Guo, Monica Agrawal
2025	J	`jnl`	Diagnosing our datasets: How does my language model learn clinical information? CoRR Furong Jia, David A. Sontag, Monica Agrawal
2025	—	`conf`	How does my language model understand clinical text? CHIL Furong Jia, David A. Sontag, Monica Agrawal
2025	—	`conf`	Position: Retrieval-augmented systems can be dangerous medical communicators. ICML (Position Papers) Lionel Wong, Ayman Ali, Raymond M. Xiong, Zejiang Shen, Yoon Kim, Monica Agrawal
2025	—	`ed.`	Proceedings of the Machine Learning for Healthcare Conference (MLHC 2025), 15-16 August 2025, Mayo Clinic, Rochester, MN, USA MLHC Monica Agrawal, Kaivalya Deshpande, Matthew Engelhard, Shalmali Joshi, Shengpu Tang, Iñigo Urteaga
2025	J	`jnl`	Retrieval-augmented systems can be dangerous medical communicators. CoRR Lionel Wong, Ayman Ali, Raymond M. Xiong, Shannon Zejiang Shen, Yoon Kim, Monica Agrawal
2025	J	`jnl`	The evaluation illusion of large language models in medicine. npj Digit. Medicine Monica Agrawal, Irene Y. Chen, Freya Gulamali, Shalmali Joshi
2024	—	`conf`	A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models. CHIL Stefan Hegselmann, Shannon Shen, Florian Gierse, Monica Agrawal, David A. Sontag, Xiaoyi Jiang
2024	J	`jnl`	A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models. CoRR Stefan Hegselmann, Shannon Zejiang Shen, Florian Gierse, Monica Agrawal, David A. Sontag, Xiaoyi Jiang
2024	J	`jnl`	Generative AI in Medicine. CoRR Divya Shanmugam, Monica Agrawal, Rajiv Movva, Irene Y. Chen, Marzyeh Ghassemi, Maia Jacobs, Emma Pierson
2024	J	`jnl`	Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study. CoRR 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
2024	J	`jnl`	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. Sharon Jiang, Barbara D. Lam, Monica Agrawal, Shannon Shen, Nicholas Kurtzman, Steven Horng, David R. Karger, David A. Sontag
2024	J	`jnl`	Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR 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
2023	—	`conf`	Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes. MLHC Sharon Jiang, Shannon Shen, Monica Agrawal, Barbara D. Lam, Nicholas Kurtzman, Steven Horng, David R. Karger, David A. Sontag
2023	J	`jnl`	Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes. CoRR Sharon Jiang, Shannon Shen, Monica Agrawal, Barbara D. Lam, Nicholas Kurtzman, Steven Horng, David R. Karger, David A. Sontag
2023	A	`conf`	TabLLM: Few-shot Classification of Tabular Data with Large Language Models. AISTATS Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David A. Sontag
2023	—	`—`	Towards Scalable Structured Data from Clinical Text Monica Agrawal
2023	J	`jnl`	Use large language models to promote equity. CoRR 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
2022	J	`jnl`	Co-training Improves Prompt-based Learning for Large Language Models. CoRR Hunter Lang, Monica Agrawal, Yoon Kim, David A. Sontag
2022	J	`jnl`	Large Language Models are Zero-Shot Clinical Information Extractors. CoRR Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David A. Sontag
2022	A*	`conf`	Large language models are few-shot clinical information extractors. EMNLP Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David A. Sontag
2022	—	`conf`	Machine Learning for Health (ML4H) 2022. ML4H@NeurIPS 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
2022	J	`jnl`	Machine Learning for Health symposium 2022 - Extended Abstract track. CoRR Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy
2022	—	`ed.`	Machine Learning for Health, ML4H 2022, 28 November 2022, New Orleans, Lousiana, USA & Virtual. ML4H@NeurIPS Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy
2022	J	`jnl`	TabLLM: Few-shot Classification of Tabular Data with Large Language Models. CoRR Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David A. Sontag
2021	A*	`conf`	Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative. CHI Ariel Levy, Monica Agrawal, Arvind Satyanarayan, David A. Sontag
2021	J	`jnl`	Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative. CoRR Ariel Levy, Monica Agrawal, Arvind Satyanarayan, David A. Sontag
2021	—	`conf`	Directing Human Attention in Event Localization for Clinical Timeline Creation. MLHC Jason Zhao, Monica Agrawal, Pedram Razavi, David A. Sontag
2021	J	`jnl`	Leveraging Time Irreversibility with Order-Contrastive Pre-training. CoRR Monica Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David A. Sontag
2021	A*	`conf`	MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records. UIST Luke S. Murray, Divya Gopinath, Monica Agrawal, Steven Horng, David A. Sontag, David R. Karger
2021	J	`jnl`	MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records. CoRR Luke S. Murray, Divya Gopinath, Monica Agrawal, Steven Horng, David A. Sontag, David R. Karger
2021	A	`conf`	PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming. AISTATS Alexander K. Lew, Monica Agrawal, David A. Sontag, Vikash Mansinghka
2020	—	`conf`	Fast, Structured Clinical Documentation via Contextual Autocomplete. MLHC Divya Gopinath, Monica Agrawal, Luke S. Murray, Steven Horng, David R. Karger, David A. Sontag
2020	J	`jnl`	Fast, Structured Clinical Documentation via Contextual Autocomplete. CoRR Divya Gopinath, Monica Agrawal, Luke S. Murray, Steven Horng, David R. Karger, David A. Sontag
2020	J	`jnl`	Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research. CoRR Benjamin Birnbaum, Nathan Nussbaum, Katharina Seidl-Rathkopf, Monica Agrawal, Melissa Estevez, Evan Estola, Joshua Haimson, Lucy He, Peter Larson, Paul Richardson
2020	J	`jnl`	PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming. CoRR Alexander K. Lew, Monica Agrawal, David A. Sontag, Vikash K. Mansinghka
2020	—	`conf`	Robust Benchmarking for Machine Learning of Clinical Entity Extraction. MLHC Monica Agrawal, Chloe O'Connell, Yasmin Fatemi, Ariel Levy, David A. Sontag
2020	J	`jnl`	Robust Benchmarking for Machine Learning of Clinical Entity Extraction. CoRR Monica Agrawal, Chloe O'Connell, Yasmin Fatemi, Ariel Levy, David A. Sontag
2020	Misc	`conf`	Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health KnowledgeGraph. PSB Irene Y. Chen, Monica Agrawal, Steven Horng, David A. Sontag
2019	J	`jnl`	Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph. CoRR Irene Y. Chen, Monica Agrawal, Steven Horng, David A. Sontag
2018	Misc	`conf`	Large-scale analysis of disease pathways in the human interactome. PSB Monica Agrawal, Marinka Zitnik, Jure Leskovec
2018	J	`jnl`	Modeling polypharmacy side effects with graph convolutional networks. Bioinform. Marinka Zitnik, Monica Agrawal, Jure Leskovec
2018	J	`jnl`	Modeling polypharmacy side effects with graph convolutional networks. CoRR Marinka Zitnik, Monica Agrawal, Jure Leskovec
2018	J	`jnl`	TIFTI: A Framework for Extracting Drug Intervals from Longitudinal Clinic Notes. CoRR Monica Agrawal, Griffin Adams, Nathan Nussbaum, Benjamin Birnbaum
2017	J	`jnl`	Large-scale analysis of disease pathways in the human interactome. CoRR Monica Agrawal, Marinka Zitnik, Jure Leskovec