Irene Y. Chen

According to our database, Irene Y. Chen authored at least 28 papers between 2018 and 2025.

Collaborative distances:

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

2025

Aggregated Individual Reporting for Post-Deployment Evaluation.

Jessica Dai, Inioluwa Deborah Raji, Benjamin Recht, Irene Y. Chen

CoRR, June, 2025

Enhancing Semi-supervised Learning with Noisy Zero-shot Pseudolabels.

Jichan Chung, Irene Y. Chen

CoRR, February, 2025

Understanding contraceptive switching rationales from real world clinical notes using large language models.

Brenda Y. Miao, Christopher Y. K. Williams, Ebenezer Chinedu-Eneh, Travis Zack, Emily Alsentzer, Atul J. Butte, Irene Y. Chen

npj Digit. Medicine, 2025

Treatment Non-Adherence Bias in Clinical Machine Learning: A Real-World Study on Hypertension Medication.

Zhongyuan Liang, Arvind Suresh, Irene Y. Chen

Proceedings of the Conference on Health, 2025

2024

Deep Speech Synthesis from Multimodal Articulatory Representations.

Peter Wu, Bohan Yu, Kevin Scheck, Alan W. Black, Aditi S. Krishnapriyan, Irene Y. Chen, Tanja Schultz, Shinji Watanabe, Gopala Krishna Anumanchipalli

CoRR, 2024

Generative AI in Medicine.

Divya Shanmugam, Monica Agrawal, Rajiv Movva, Irene Y. Chen, Marzyeh Ghassemi, Maia Jacobs, Emma Pierson

CoRR, 2024

A large language model-based approach to quantifying the effects of social determinants in liver transplant decisions.

Emily Robitschek, Asal Bastani, Kathryn Horwath, Savyon Sordean, Mark J. Pletcher, Jennifer C. Lai, Sergio Galletta, Elliott Ash, Jin Ge, Irene Y. Chen

CoRR, 2024

Access to care improves EHR reliability and clinical risk prediction model performance.

Anna Zink, Hongzhou Luan, Irene Y. Chen

CoRR, 2024

Updating the Minimum Information about CLinical Artificial Intelligence (MI-CLAIM) checklist for generative modeling research.

Brenda Y. Miao, Irene Y. Chen, Christopher Y. K. Williams, Jaysón M. Davidson, Augusto Garcia-Agundez, Harry Sun, Travis Zack, Atul J. Butte, Madhumita Sushil

CoRR, 2024

Identifying Reasons for Contraceptive Switching from Real-World Data Using Large Language Models.

Brenda Y. Miao, Christopher Y. K. Williams, Ebenezer Chinedu-Eneh, Travis Zack, Emily Alsentzer, Atul J. Butte, Irene Y. Chen

CoRR, 2024

The Data Addition Dilemma.

Judy Hanwen Shen, Inioluwa Deborah Raji, Irene Y. Chen

Proceedings of the Machine Learning for Healthcare Conference, 2024

NLP for Maternal Healthcare: Perspectives and Guiding Principles in the Age of LLMs.

Maria Antoniak, Aakanksha Naik, Carla S. Alvarado, Lucy Lu Wang, Irene Y. Chen

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

Conference on Health, Inference, and Learning (CHIL) 2024.

Tom J. Pollard, Edward Choi, Pankhuri Singhal, Michael C. Hughes, Elena Sizikova, Bobak Mortazavi, Irene Y. Chen, Fei Wang, Tasmie Sarker, Matthew B. A. McDermott, Marzyeh Ghassemi

Proceedings of the Conference on Health, 2024

2023

Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health.

Maria Antoniak, Aakanksha Naik, Carla S. Alvarado, Lucy Lu Wang, Irene Y. Chen

CoRR, 2023

Generating Drug Repurposing Hypotheses through the Combination of Disease-Specific Hypergraphs.

Ayush Jain, Marie-Laure Charpignon, Irene Y. Chen, Anthony Philippakis, Ahmed M. Alaa

CoRR, 2023

Closing the Gap in High-Risk Pregnancy Care Using Machine Learning and Human-AI Collaboration.

Hussein Mozannar, Yuria Utsumi, Irene Y. Chen, Stephanie S. Gervasi, Michele Ewing, Aaron Smith-McLallen, David A. Sontag

CoRR, 2023

2022

Machine Learning Approaches for Equitable Healthcare

Irene Y. Chen

PhD thesis, 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

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

Clustering Interval-Censored Time-Series for Disease Phenotyping.

Irene Y. Chen, Rahul G. Krishnan, David A. Sontag

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Clustering Left-Censored Multivariate Time-Series.

Irene Y. Chen, Rahul G. Krishnan, David A. Sontag

CoRR, 2021

CheXclusion: Fairness gaps in deep chest X-ray classifiers.

Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew B. A. McDermott, Irene Y. Chen, Marzyeh Ghassemi

Proceedings of the Biocomputing 2021: Proceedings of the Pacific Symposium, 2021

Intimate Partner Violence and Injury Prediction From Radiology Reports.

Irene Y. Chen, Emily Alsentzer, Hyesun Park, Richard Thomas, Babina Gosangi, Rahul Gujrathi, Bharti Khurana

Proceedings of the Biocomputing 2021: Proceedings of the Pacific Symposium, 2021

2020

Probabilistic Machine Learning for Healthcare.

Irene Y. Chen, Shalmali Joshi, Marzyeh Ghassemi, Rajesh Ranganath

CoRR, 2020

Ethical Machine Learning in Health Care.

Irene Y. Chen, Emma Pierson, Sherri Rose, Shalmali Joshi, Kadija Ferryman, Marzyeh Ghassemi

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

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

Why Is My Classifier Discriminatory?

Irene Y. Chen, Fredrik D. Johansson, David A. Sontag

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018