Categorizing Emails Using Machine Learning with Textual Features. - Haoran Zhang 003; Jagadish Rangrej; Saad Rais; Michael Hillmer; Frank Rudzicz; Kamil Malikov (Canadian AI, 2019)

Hurtful words: quantifying biases in clinical contextual word embeddings. - Haoran Zhang 003; Amy X. Lu; Mohamed Abdalla 001; Matthew B. A. McDermott; Marzyeh Ghassemi (CHIL, 2020)

An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare. - Taylor W. Killian; Haoran Zhang 003; Jayakumar Subramanian; Mehdi Fatemi; Marzyeh Ghassemi (ML4H@NeurIPS, 2020)

An empirical framework for domain generalization in clinical settings. - Haoran Zhang 003; Natalie Dullerud; Laleh Seyyed-Kalantari; Quaid Morris; Shalmali Joshi; Marzyeh Ghassemi (CHIL, 2021)

Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. - Sindhu C. M. Gowda; Shalmali Joshi; Haoran Zhang 003; Marzyeh Ghassemi (CIKM, 2021)

Learning Optimal Predictive Checklists. - Haoran Zhang 003; Quaid Morris; Berk Ustun; Marzyeh Ghassemi (NeurIPS, 2021)

Reading Race: AI Recognises Patient's Racial Identity In Medical Images. - Imon Banerjee; Ananth Reddy Bhimireddy; John L. Burns; Leo Anthony Celi; Li-Ching Chen; Ramon Correa; Natalie Dullerud; Marzyeh Ghassemi; Shih-Cheng Huang; Po-Chih Kuo; Matthew P. Lungren; Lyle J. Palmer; et al. (CoRR, 2021)

A comparison of approaches to improve worst-case predictive model performance over patient subpopulations. - Stephen R. Pfohl; Haoran Zhang 003; Yizhe Xu; Agata Foryciarz; Marzyeh Ghassemi; Nigam H. Shah (CoRR, 2021)

Improving the Fairness of Chest X-ray Classifiers. - Haoran Zhang 003; Natalie Dullerud; Karsten Roth; Lauren Oakden-Rayner; Stephen Pfohl; Marzyeh Ghassemi (CHIL, 2022)

The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations. - Aparna Balagopalan; Haoran Zhang 003; Kimia Hamidieh; Thomas Hartvigsen; Frank Rudzicz; Marzyeh Ghassemi (FAccT, 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)

PAN-cODE: COVID-19 forecasting using conditional latent ODEs. - Ruian Shi; Haoran Zhang 003; Quaid Morris (J. Am. Medical Informatics Assoc., 2022)

Change is Hard: A Closer Look at Subpopulation Shift. - Yuzhe Yang 003; Haoran Zhang 003; Dina Katabi; Marzyeh Ghassemi (ICML, 2023)

"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. - Haoran Zhang 003; Harvineet Singh; Marzyeh Ghassemi; Shalmali Joshi (ICML, 2023)

Machine Learning for Health (ML4H) 2023. - Stefan Hegselmann; Antonio Parziale; Divya Shanmugam; Shengpu Tang; Kristen Severson 001; Mercy Nyamewaa Asiedu; Serina Chang; Bonaventure F. P. Dossou; Qian Huang; Fahad Kamran; Haoran Zhang 003; Sujay Nagaraj; et al. (ML4H@NeurIPS, 2023)

Continuous Time Evidential Distributions for Irregular Time Series. - Taylor W. Killian; Haoran Zhang 003; Thomas Hartvigsen; Ava P. Amini (CoRR, 2023)

The Limits of Fair Medical Imaging AI In The Wild. - Yuzhe Yang 003; Haoran Zhang 003; Judy W. Gichoya; Dina Katabi; Marzyeh Ghassemi (CoRR, 2023)

Identifying Implicit Social Biases in Vision-Language Models. - Kimia Hamidieh; Haoran Zhang 003; Walter Gerych; Thomas Hartvigsen; Marzyeh Ghassemi (AIES (1), 2024)

Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation. - Kimia Hamidieh; Haoran Zhang 003; Swami Sankaranarayanan; Marzyeh Ghassemi (ICLR, 2024)

Machine Learning for Health (ML4H) 2024. - Helen Zhou; Stefan Hegselmann; Elizabeth Healey; Trenton Chang; Caleb Ellington; Michael Leone; Vishwali Mhasawade; Sana Tonekaboni; Winston Chen; Hyewon Jeong; Xiaoxiao Li; Juyeon Heo; et al. (ML4H@NeurIPS, 2024)

BendVLM: Test-Time Debiasing of Vision-Language Embeddings. - Walter Gerych; Haoran Zhang 003; Kimia Hamidieh; Eileen Pan; Maanas K. Sharma; Tom Hartvigsen; Marzyeh Ghassemi (NeurIPS, 2024)

A Closer Look at AUROC and AUPRC under Class Imbalance. - Matthew B. A. McDermott; Haoran Zhang 003; Lasse Hyldig Hansen; Giovanni Angelotti; Jack Gallifant (NeurIPS, 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)

LEMoN: Label Error Detection using Multimodal Neighbors. - Haoran Zhang 003; Aparna Balagopalan; Nassim Oufattole; Hyewon Jeong; Yan Wu; Jiacheng Zhu; Marzyeh Ghassemi (CoRR, 2024)

Machine Learning for Health symposium 2024 - Findings track. - Stefan Hegselmann; Helen Zhou; Elizabeth Healey; Trenton Chang; Caleb Ellington; Vishwali Mhasawade; Sana Tonekaboni; Peniel N. Argaw; Haoran Zhang 003 (CoRR, 2025)

MedPAIR: Measuring Physicians and AI Relevance Alignment in Medical Question Answering. - Yuexing Hao; Kumail Alhamoud; Hyewon Jeong; Haoran Zhang 003; Isha Puri; Philip Torr 001; Mike Schaekermann; Ariel D. Stern; Marzyeh Ghassemi (CoRR, 2025)