Agrawal, Monica

Modeling polypharmacy side effects with graph convolutional networks

Zitnik, M., Agrawal, M., & Leskovec, J. (2018) · Bioinformatics

Computational Drug Discovery MethodsPharmacovigilance and Adverse Drug Reactions

Cited by 1,501

Large language models are few-shot clinical information extractors

Agrawal, M., Hegselmann, S., Lang, H., Kim, Y., & Sontag, D. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Machine Learning in HealthcareTopic Modeling

Cited by 358

Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative

Levy, A., Agrawal, M., Satyanarayan, A., & Sontag, D. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Human-Automation Interaction and SafetyExplainable Artificial Intelligence (XAI)

Cited by 73

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

Hegselmann, S., Shen, S. Z., Gierse, F., Agrawal, M., Sontag, D., & Jiang, X. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 6

Retrieval-augmented systems can be dangerous medical communicators

Wong, L., Ali, A., Xiong, R., Shen, S. Z., Kim, Y., & Agrawal, M. (2025) · arXiv

Artificial Intelligence in Healthcare and EducationHealth Literacy and Information Accessibility

Cited by 5