research

2026

1. 

   Aggregated Individual Reporting for Post-Deployment Evaluation

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

   ICML, 2026

   PDF

2. 

   Falsifying Sparse Autoencoder Reasoning Features in Language Models

   George Ma, Zhongyuan Liang, Irene Y. Chen, and Somayeh Sojoudi

   ICML, 2026

   PDF

3. 

   Uncertainty Drives Social Bias Changes in Quantized Large Language Models

   Stanley Z. Hua, Sanae Lotfi, and Irene Y. Chen

   COLM, 2026

   PDF

4. 

   Enhancing Semi-supervised Learning with Zero-shot Pseudolabels

   Jichan Chung, and Irene Y. Chen

   Transactions on Machine Learning Research, 2026

   HTML

5. 

   OC-Distill: Ontology-aware Contrastive Learning with Cross-Modal Distillation for ICU Risk Prediction

   Zhongyuan Liang, Junhyung Jo, Hyang-Jung Lee, Sang Kyu Kim, and Irene Y. Chen

   MLHC, 2026

   PDF

6. 

   Investigating Data Interventions for Subgroup Fairness: An ICU Case Study

   Erin Tan, Judy Hanwen Shen, and Irene Y. Chen

   ICLR Workshop on Principled Design for Trustworthy AI, 2026

   PDF

2025

1. 

   The evaluation illusion of large language models in medicine

   Monica Agrawal, Irene Y. Chen, Freya Gulamali, and Shalmali Joshi

   npj Digital Medicine, 2025

   HTML

2. 

   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, and Irene Y. Chen

   npj Digital Medicine, 2025

   HTML

3. 

   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, and Irene Y. Chen

   npj Digital Medicine, 2025

   HTML

4. 

   Quantifying device type and handedness biases in a remote Parkinson’s disease AI-powered assessment

   Zerin Nasrin Tumpa, Md Rahat Shahriar Zawad, Lydia Sollis, Shubham Parab, Irene Y. Chen, and Peter Washington

   npj Digital Medicine, 2025

   HTML

5. 

   Bridging Research Gaps Between Academic Research and Legal Investigations of Algorithmic Discrimination

   Colleen V. Chien, Anna Zink, and Irene Y. Chen

   In AIES, 2025

   HTML

6. 

   Dataset-to-Dataset Evaluation Before (and Without) Sharing Data

   Keren Fuentes, Mimee Xu, and Irene Y. Chen

   In AIES, 2025

   HTML

7. 

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

   Zhongyuan Liang, Arvind Suresh, and Irene Y. Chen

   In CHIL, 2025

   HTML

8. 

   Patient Safety Risks from AI Scribes: Signals from End-User Feedback

   Jessica Dai, Anwen Huang, Catherine Nasrallah, Rhiannon Croci, Hossein Soleimani, Sarah J. Pollet, Julia Adler-Milstein, Sara G. Murray, Jinoos Yazdany, and Irene Y. Chen

   ML4H, 2025

   PDF

9. 

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

   Anna Zink, Hongzhou Luan, and Irene Y. Chen

   Nature Health, 2025

   PDF

2024

1. 

   The Data Addition Dilemma

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

   MLHC, 2024

   PDF

2. 

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

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

   FAccT, 2024

   PDF

3. 

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

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

   npj Digital Medicine, 2024

4. 

   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, and Madhumita Sushil

   Nature Medicine, 2024

   PDF

5. 

   Generative AI in Medicine

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

   Annual Reviews of Biomedical Data Science, 2024

   PDF

6. 

   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, and Gopala Krishna Anumanchipalli

   ISCA, 2024

   PDF

2023

1. 

   Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes

   May Yee Choi, Irene Y Chen, Ann Elaine Clarke, Marvin J Fritzler, Katherine A Buhler, Murray Urowitz, John Hanly, Yvan St-Pierre, Caroline Gordon, Sang-Cheol Bae, and  others

   Annals of the Rheumatic Diseases, 2023

   HTML

2. 

   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, and David Sontag

   arXiv preprint arXiv:2305.17261, 2023

   PDF

3. 

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

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

   PSB, 2023

   PDF

2022

1. 

   The Potential For Bias In Machine Learning And Opportunities For Health Insurers To Address It

   Stephanie S Gervasi, Irene Y Chen, Aaron Smith-McLallen, David Sontag, Ziad Obermeyer, Michael Vennera, and Ravi Chawla

   Health Affairs, 2022

   HTML

2. 

   Clustering Interval-Censored Time-Series for Disease Phenotyping

   Irene Y Chen, Rahul G Krishnan, and David Sontag

   In Proceedings of the AAAI Conference on Artificial Intelligence, 2022

   PDF

3. 

   Machine Learning Approaches for Equitable Healthcare

   Irene Y Chen

   Massachusetts Institute of Technology, 2022

   PDF

2021

1. 

   Recognizing isolated ulnar fractures as potential markers for intimate partner violence

   Bharti Khurana, David Sing, Rahul Gujrathi, Abhishek Keraliya, Camden P Bay, Irene Chen, Steven E Seltzer, Giles W Boland, Mitchel B Harris, George SM Dyer, and  others

   Journal of the American College of Radiology, 2021

   HTML

2. 

   Longitudinal imaging history in early identification of intimate partner violence

   Hyesun Park, Rahul Gujrathi, Babina Gosangi, Richard Thomas, Tianxi Cai, Irene Chen, Camden Bay, Najmo Hassan, Giles Boland, Isaac Kohane, and  others

   European radiology, 2021

   HTML

3. 

   Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations

   Laleh Seyyed-Kalantari, Haoran Zhang, Matthew BA McDermott, Irene Y Chen, and Marzyeh Ghassemi

   Nature medicine, 2021

   HTML

2020

1. 

   Treating health disparities with artificial intelligence

   Irene Y Chen, Shalmali Joshi, and Marzyeh Ghassemi

   Nature medicine, 2020

   HTML

2. 

   A review of challenges and opportunities in machine learning for health

   Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L Beam, Irene Y Chen, and Rajesh Ranganath

   AMIA Summits on Translational Science Proceedings, 2020

   HTML

3. 

   Intimate Partner Violence and Injury Prediction From Radiology Reports

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

   In Pacific Symposium of Biocomputing 2021, 2020

   PDF

4. 

   Probabilistic Machine Learning for Healthcare

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

   Annual Review of Biomedical Data Science, 2020

   PDF

5. 

   CheXclusion: Fairness gaps in deep chest X-ray classifiers

   Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew McDermott, Irene Y Chen, and Marzyeh Ghassemi

   In Pacific Symposium of Biocomputing 2021, 2020

   PDF

6. 

   Ethical Machine Learning in Health

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

   Annual Review of Biomedical Data Science 4, 2020

   PDF

2019

1. 

   Can AI Help Reduce Disparities in General Medical and Mental Health Care?

   Irene Y Chen, Peter Szolovits, and Marzyeh Ghassemi

   AMA Journal of Ethics, 2019

   HTML

2. 

   Practical guidance on artificial intelligence for health-care data

   Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L Beam, Irene Y Chen, and Rajesh Ranganath

   The Lancet Digital Health, 2019

   HTML

3. 

   We should treat algorithms like prescription drugs

   Andy Coravos, Irene Chen, Ankit Gordhandas, and Ariel Dora Stern

   2019

   HTML

4. 

   Turning the crank for machine learning: ease, at what expense?

   Tom J Pollard, Irene Chen, Jenna Wiens, Steven Horng, Danny Wong, Marzyeh Ghassemi, Heather Mattie, Emily Lindemer, and Trishan Panch

   The Lancet Digital Health, 2019

   HTML

5. 

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

   Irene Y Chen, Monica Agrawal, Steven Horng, and David Sontag

   In Pacific Symposium of Biocomputing 2020, 2019

   PDF

6. 

   Trends and focus of machine learning applications for health research

   Brett Beaulieu-Jones, Samuel G Finlayson, Corey Chivers, Irene Chen, Matthew McDermott, Jaz Kandola, Adrian V Dalca, Andrew Beam, Madalina Fiterau, and Tristan Naumann

   JAMA network open, 2019

   HTML

2018

1. 

   Why Is My Classifier Discriminatory?

   Irene Y Chen, Fredrik D Johansson, and David Sontag

   In Neural Information Processing Systems (NeurIPS) 2018, 2018

   PDF