Probabilistically Populated Medical Record Templates: Reducing Clinical Documentation Time Using Patient Cooperation. - Tristan Naumann; Marzyeh Ghassemi; Andreea Bodnari; Rohit Joshi (AMIA, 2013)

Unfolding physiological state: mortality modelling in intensive care units. - Marzyeh Ghassemi; Tristan Naumann; Finale Doshi-Velez; Nicole Brimmer; Rohit Joshi; Anna Rumshisky; Peter Szolovits (KDD, 2014)

Learning to Detect Vocal Hyperfunction From Ambulatory Neck-Surface Acceleration Features: Initial Results for Vocal Fold Nodules. - Marzyeh Ghassemi; Jarrad H. Van Stan; Daryush D. Mehta; Matías Zanartu; Harold A. Cheyne II; Robert E. Hillman; John V. Guttag (IEEE Trans. Biomed. Eng., 2014)

A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data. - Marzyeh Ghassemi; Marco A. F. Pimentel; Tristan Naumann; Thomas Brennan; David A. Clifton; Peter Szolovits; Mengling Feng (AAAI, 2015)

Corrections to "Learning to Detect Vocal Hyperfunction From Ambulatory Neck-Surface Acceleration Features: Initial Results For Vocal Fold Nodules". - Marzyeh Ghassemi; Jarrad H. Van Stan; Daryush D. Mehta; Matías Zanartu; Harold A. Cheyne II; Robert E. Hillman; John V. Guttag (IEEE Trans. Biomed. Eng., 2015)

Prediction using patient comparison vs. modeling: A case study for mortality prediction. - Mark Hoogendoorn; Ali el Hassouni; Kwongyen Mok; Marzyeh Ghassemi; Peter Szolovits (EMBC, 2016)

Uncovering Voice Misuse Using Symbolic Mismatch. - Marzyeh Ghassemi; Zeeshan Syed; Daryush D. Mehta; Jarrad H. Van Stan; Robert E. Hillman; John V. Guttag (MLHC, 2016)

Predicting intervention onset in the ICU with switching state space models. - Marzyeh Ghassemi; Mike Wu; Michael C. Hughes; Peter Szolovits; Finale Doshi-Velez (CRI, 2017)

Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach. - Aniruddh Raghu; Matthieu Komorowski; Leo Anthony Celi; Peter Szolovits; Marzyeh Ghassemi (MLHC, 2017)

Clinical Intervention Prediction and Understanding with Deep Neural Networks. - Harini Suresh; Nathan Hunt; Alistair E. W. Johnson; Leo Anthony Celi; Peter Szolovits; Marzyeh Ghassemi (MLHC, 2017)

Clinical Intervention Prediction and Understanding using Deep Networks. - Harini Suresh; Nathan Hunt; Alistair E. W. Johnson; Leo Anthony Celi; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2017)

The Use of Autoencoders for Discovering Patient Phenotypes. - Harini Suresh; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2017)

Deep Reinforcement Learning for Sepsis Treatment. - Aniruddh Raghu; Matthieu Komorowski; Imran Ahmed; Leo A. Celi; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2017)

Short-term Mortality Prediction for Elderly Patients Using Medicare Claims Data. - Maggie Makar; Marzyeh Ghassemi; David Cutler; Ziad Obermeyer (CoRR, 2017)

Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database. - Mike Wu; Marzyeh Ghassemi; Mengling Feng; Leo A. Celi; Peter Szolovits; Finale Doshi-Velez (J. Am. Medical Informatics Assoc., 2017)

Representation learning in multi-dimensional clinical timeseries for risk and event prediction. - Marzyeh Ghassemi (2017)

Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs. - Matthew B. A. McDermott; Tom Yan; Tristan Naumann; Nathan Hunt; Harini Suresh; Peter Szolovits; Marzyeh Ghassemi (AAAI, 2018)

Racial Disparities and Mistrust in End-of-Life Care. - Willie Boag; Harini Suresh; Leo Anthony Celi; Peter Szolovits; Marzyeh Ghassemi (MLHC, 2018)

Opportunities in Machine Learning for Healthcare. - Marzyeh Ghassemi; Tristan Naumann; Peter Schulam; Andrew L. Beam; Rajesh Ranganath (CoRR, 2018)

Modeling Mistrust in End-of-Life Care. - Willie Boag; Harini Suresh; Leo Anthony Celi; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2018)

ClinicalVis: Supporting Clinical Task-Focused Design Evaluation. - Marzyeh Ghassemi; Mahima Pushkarna; James Wexler; Jesse Johnson; Paul Varghese (CoRR, 2018)

Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. - Natalia Antropova; Andrew L. Beam; Brett K. Beaulieu-Jones; Irene Chen; Corey Chivers; Adrian V. Dalca; Samuel G. Finlayson; Madalina Fiterau; Jason Alan Fries; Marzyeh Ghassemi; Mike Hughes; Bruno Jedynak; et al. (CoRR, 2018)

The Effect of Heterogeneous Data for Alzheimer's Disease Detection from Speech. - Aparna Balagopalan; Jekaterina Novikova; Frank Rudzicz; Marzyeh Ghassemi (CoRR, 2018)

Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation. - Bret Nestor; Matthew B. A. McDermott; Geeticka Chauhan; Tristan Naumann; Michael C. Hughes; Anna Goldenberg; Marzyeh Ghassemi (CoRR, 2018)

Reproducibility in Machine Learning for Health. - Matthew B. A. McDermott; Shirly Wang; Nikki Marinsek; Rajesh Ranganath; Marzyeh Ghassemi; Luca Foschini 002 (RML@ICLR, 2019)

Clinically Accurate Chest X-Ray Report Generation. - Guanxiong Liu; Tzu-Ming Harry Hsu; Matthew B. A. McDermott; Willie Boag; Wei-Hung Weng; Peter Szolovits; Marzyeh Ghassemi (MLHC, 2019)

Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. - Bret Nestor; Matthew B. A. McDermott; Willie Boag; Gabriela Berner; Tristan Naumann; Michael C. Hughes; Anna Goldenberg; Marzyeh Ghassemi (MLHC, 2019)

Learning from Few Subjects with Large Amounts of Voice Monitoring Data. - Jose Javier Gonzalez Ortiz; Daryush D. Mehta; Jarrad H. Van Stan; Robert E. Hillman; John V. Guttag; Marzyeh Ghassemi (MLHC, 2019)

Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation. - Aparna Balagopalan; Jekaterina Novikova; Matthew B. A. McDermott; Bret Nestor; Tristan Naumann; Marzyeh Ghassemi (ML4H@NeurIPS, 2019)

The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers. - Alex X. Lu; Amy X. Lu; Wiebke Schormann; Marzyeh Ghassemi; David W. Andrews; Alan M. Moses (NeurIPS, 2019)

Modeling the Biological Pathology Continuum with HSIC-regularized Wasserstein Auto-encoders. - Denny Wu; Hirofumi Kobayashi; Charles Ding; Cheng Lei; Keisuke Goda; Marzyeh Ghassemi (CoRR, 2019)

Multiple Sclerosis Severity Classification From Clinical Text. - Alister D. Costa; Stefan Denkovski; Michal Malyska; Sae Young Moon; Brandon Rufino; Zhen Yang; Taylor W. Killian; Marzyeh Ghassemi (ClinicalNLP@EMNLP, 2020)

MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III. - Shirly Wang; Matthew B. A. McDermott; Geeticka Chauhan; Marzyeh Ghassemi; Michael C. Hughes; Tristan Naumann (CHIL, 2020)

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)

SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness. - Nathan Ng 001; Kyunghyun Cho; Marzyeh Ghassemi (EMNLP (1), 2020)

CheXpert++: Approximating the CheXpert Labeler for Speed, Differentiability, and Probabilistic Output. - Matthew B. A. McDermott; Tzu-Ming Harry Hsu; Wei-Hung Weng; Marzyeh Ghassemi; Peter Szolovits (MLHC, 2020)

Preparing a Clinical Support Model for Silent Mode in General Internal Medicine. - Bret Nestor; Liam G. McCoy; Amol Verma; Chloé Pou-Prom; Joshua Murray; Sebnem Kuzulugil; David Dai; Muhammad Mamdani; Anna Goldenberg; Marzyeh Ghassemi (MLHC, 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)

Confounding Feature Acquisition for Causal Effect Estimation. - Shirly Wang; Seung Eun Yi; Shalmali Joshi; Marzyeh Ghassemi (ML4H@NeurIPS, 2020)

CheXclusion: Fairness gaps in deep chest X-ray classifiers. - Laleh Seyyed-Kalantari; Guanxiong Liu; Matthew B. A. McDermott; Marzyeh Ghassemi (CoRR, 2020)

Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning. - Joseph Paul Cohen; Lan Dao; Paul Morrison; Karsten Roth; Yoshua Bengio; Beiyi Shen; Almas Abbasi; Mahsa Hoshmand-Kochi; Marzyeh Ghassemi; Haifang Li; Tim Q. Duong (CoRR, 2020)

COVID-19 Image Data Collection: Prospective Predictions Are the Future. - Joseph Paul Cohen; Paul Morrison; Lan Dao; Karsten Roth; Tim Q. Duong; Marzyeh Ghassemi (CoRR, 2020)

A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data. - Matthew B. A. McDermott; Bret Nestor; Evan Kim; Wancong Zhang; Anna Goldenberg; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2020)

S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. - Karsten Roth; Timo Milbich; Björn Ommer; Joseph Paul Cohen; Marzyeh Ghassemi (CoRR, 2020)

Ethical Machine Learning in Health Care. - Irene Y. Chen; Emma Pierson; Sherri Rose; Shalmali Joshi; Kadija Ferryman; Marzyeh Ghassemi (CoRR, 2020)

Probabilistic Machine Learning for Healthcare. - Irene Y. Chen; Shalmali Joshi; Marzyeh Ghassemi; Rajesh Ranganath (CoRR, 2020)

Improving Dialogue Breakdown Detection with Semi-Supervised Learning. - Nathan Ng 001; Marzyeh Ghassemi; Narendran Thangarajan; Jiacheng Pan; Qi Guo (CoRR, 2020)

Making Health AI Work in the Real World: Strategies, innovations, and best practices for using AI to improve care delivery. - Suchi Saria; Marzyeh Ghassemi; Ziad Obermeyer; Karandeep Singh; Pei-Yun S. Hsueh; Eric J. Topol (AMIA, 2021)

A comprehensive EHR timeseries pre-training benchmark. - Matthew B. A. McDermott; Bret Nestor; Evan Kim; Wancong Zhang; Anna Goldenberg; Peter Szolovits; Marzyeh Ghassemi (CHIL, 2021)

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)

Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness. - Victoria Cheng; Vinith M. Suriyakumar; Natalie Dullerud; Shalmali Joshi; Marzyeh Ghassemi (FAccT, 2021)

Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. - Vinith M. Suriyakumar; Nicolas Papernot; Anna Goldenberg; Marzyeh Ghassemi (FAccT, 2021)

Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. - Karsten Roth; Timo Milbich; Björn Ommer; Joseph Paul Cohen; Marzyeh Ghassemi (ICML, 2021)

Medical Dead-ends and Learning to Identify High-Risk States and Treatments. - Mehdi Fatemi; Taylor W. Killian; Jayakumar Subramanian; Marzyeh Ghassemi (NeurIPS, 2021)

Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. - Timo Milbich; Karsten Roth; Samarth Sinha; Ludwig Schmidt; Marzyeh Ghassemi; Björn Ommer (NeurIPS, 2021)

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

CheXclusion: Fairness gaps in deep chest X-ray classifiers. - Laleh Seyyed-Kalantari; Guanxiong Liu; Matthew B. A. McDermott; Irene Y. Chen; Marzyeh Ghassemi (PSB, 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)

Quantifying the Task-Specific Information in Text-Based Classifications. - Zining Zhu 001; Aparna Balagopalan; Marzyeh Ghassemi; Frank Rudzicz (CoRR, 2021)

Do as AI say: susceptibility in deployment of clinical decision-aids. - Susanne Gaube; Harini Suresh; Martina Raue; Alexander Merritt; Seth J. Berkowitz; Eva Lermer; Joseph F. Coughlin; John V. Guttag; Errol Colak; Marzyeh Ghassemi (npj Digit. Medicine, 2021)

Write It Like You See It: Detectable Differences in Clinical Notes by Race Lead to Differential Model Recommendations. - Hammaad Adam; Ming-Ying Yang; Kenrick Cato; Ioana Baldini; Charles Senteio; Leo Anthony Celi; Jiaming Zeng; Moninder Singh; Marzyeh Ghassemi (AIES, 2022)

Get To The Point! Problem-Based Curated Data Views To Augment Care For Critically Ill Patients. - Minfan Zhang; Daniel Ehrmann; Mjaye Mazwi; Danny Eytan; Marzyeh Ghassemi; Fanny Chevalier (CHI, 2022)

Semi-Markov Offline Reinforcement Learning for Healthcare. - Mehdi Fatemi; Mary Wu; Jeremy Petch; Walter Nelson; Stuart J. Connolly; Alexander Benz; Anthony Carnicelli; Marzyeh Ghassemi (CHIL, 2022)

Counterfactually Guided Policy Transfer in Clinical Settings. - Taylor W. Killian; Marzyeh Ghassemi; Shalmali Joshi (CHIL, 2022)

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

Uniform Priors for Data-Efficient Learning. - Samarth Sinha; Karsten Roth; Anirudh Goyal; Marzyeh Ghassemi; Zeynep Akata; Hugo Larochelle; Animesh Garg (CVPR Workshops, 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)

Understanding the Variance Collapse of SVGD in High Dimensions. - Jimmy Ba; Murat A. Erdogdu; Marzyeh Ghassemi; Shengyang Sun; Taiji Suzuki; Denny Wu; Tianzong Zhang (ICLR, 2022)

Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. - Rob Brekelmans; Sicong Huang 001; Marzyeh Ghassemi; Greg Ver Steeg; Roger Baker Grosse; Alireza Makhzani (ICLR, 2022)

Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning. - Natalie Dullerud; Karsten Roth; Kimia Hamidieh; Nicolas Papernot; Marzyeh Ghassemi (ICLR, 2022)

If Influence Functions are the Answer, Then What is the Question? - Juhan Bae; Nathan Ng 001; Alston Lo; Marzyeh Ghassemi; Roger B. Grosse (NeurIPS, 2022)

When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction. - Vinith M. Suriyakumar; Marzyeh Ghassemi; Berk Ustun (CoRR, 2022)

Predicting Out-of-Domain Generalization with Local Manifold Smoothness. - Nathan Ng 001; Neha Hulkund; Kyunghyun Cho; Marzyeh Ghassemi (CoRR, 2022)

Decision-centered design of a clinical decision support system for acute management of pediatric congenital heart disease. - Azadeh Assadi; Peter C. Laussen; Gabrielle Freire; Marzyeh Ghassemi; Patricia Trbovich (Frontiers Digit. Health, 2022)

Machine learning and health need better values. - Marzyeh Ghassemi; Shakir Mohamed (npj Digit. Medicine, 2022)

Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum. - Sarah M. Goodday; E. Karlin; A. Brooks; C. Chapman; Daniel R. Karlin; Luca Foschini 002; E. Kipping; M. Wildman; M. Francis; H. Greenman; Li Li 062; Eric E. Schadt; et al. (npj Digit. Medicine, 2022)

In medicine, how do we machine learn anything real? - Marzyeh Ghassemi; Elaine O. Nsoesie (Patterns, 2022)

Evaluating the Impact of Social Determinants on Health Prediction in the Intensive Care Unit. - Ming-Ying Yang; Gloria Hyun-Jung Kwak; Tom J. Pollard; Leo Anthony Celi; Marzyeh Ghassemi (AIES, 2023)

Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward. - Anja Thieme; Aditya V. Nori; Marzyeh Ghassemi; Rishi Bommasani; Tariq Osman Andersen; Ewa Luger (CHI Extended Abstracts, 2023)

Clinical Relevance Score for Guided Trauma Injury Pattern Discovery with Weakly Supervised β-VAE. - Qixuan Jin; Jacobien H. F. Oosterhoff; Yepeng Huang; Marzyeh Ghassemi; Gabriel A Brat (CHIL, 2023)

Taking Off with AI: Lessons from Aviation for Healthcare. - Elizabeth Bondi-Kelly; Thomas Hartvigsen; Lindsay M. Sanneman; Swami Sankaranarayanan; Zach Harned; Grace Wickerson; Judy Wawira Gichoya; Lauren Oakden-Rayner; Leo Anthony Celi; Matthew P. Lungren; Julie A. Shah; Marzyeh Ghassemi (EAAMO, 2023)

In the Name of Fairness: Assessing the Bias in Clinical Record De-identification. - Yuxin Xiao; Shulammite Lim; Tom Joseph Pollard; Marzyeh Ghassemi (FAccT, 2023)

When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction. - Vinith Menon Suriyakumar; Marzyeh Ghassemi; Berk Ustun (ICML, 2023)

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)

Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals. - Hyewon Jeong; Collin M. Stultz; Marzyeh Ghassemi (MLHC, 2023)

Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors. - Tom Hartvigsen; Swami Sankaranarayanan; Hamid Palangi; Yoon Kim; Marzyeh Ghassemi (NeurIPS, 2023)

VisAlign: Dataset for Measuring the Alignment between AI and Humans in Visual Perception. - Jiyoung Lee; Seungho Kim; Seunghyun Won; Joonseok Lee; Marzyeh Ghassemi; James Thorne; Jaeseok Choi; O.-Kil Kwon; Edward Choi (NeurIPS, 2023)

Evaluating the Impact of Social Determinants on Health Prediction. - Ming-Ying Yang; Gloria Hyun-Jung Kwak; Tom J. Pollard; Leo Anthony Celi; Marzyeh Ghassemi (CoRR, 2023)

VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception. - Jiyoung Lee; Seungho Kim; Seunghyun Won; Joonseok Lee; Marzyeh Ghassemi; James Thorne; Jaeseok Choi; O.-Kil Kwon; Edward Choi (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)

Event-Based Contrastive Learning for Medical Time Series. - Hyewon Jeong; Nassim Oufattole; Aparna Balagopalan; Matthew B. A. McDermott; Payal Chandak; Marzyeh Ghassemi; Collin M. Stultz (CoRR, 2023)

Dissecting the heterogeneity of "in the wild" stress from multimodal sensor data. - Sujay Nagaraj; Sarah M. Goodday; Thomas Hartvigsen; Adrien Boch; Kopal Garg; Sindhu C. M. Gowda; Luca Foschini 002; Marzyeh Ghassemi; Stephen H. Friend; Anna Goldenberg (npj Digit. Medicine, 2023)

Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning. - Taylor W. Killian; Sonali Parbhoo; Marzyeh Ghassemi (Trans. Mach. Learn. Res., 2023)

Predicting Out-of-Domain Generalization with Neighborhood Invariance. - Nathan H. Ng; Neha Hulkund; Kyunghyun Cho; Marzyeh Ghassemi (Trans. Mach. Learn. Res., 2023)

The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols. - Paula Dhiman; Rebecca Whittle; Ben Van Calster; Marzyeh Ghassemi; Xiaoxuan Liu; Melissa D. McCradden; Karel G. M. Moons; Richard D. Riley; Gary S. Collins (Nat. Mac. Intell., 2023)

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

Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention. - Adiba Orzikulova; Han Xiao; Zhipeng Li 001; Yukang Yan; Yuntao Wang 001; Yuanchun Shi; Marzyeh Ghassemi; Sung-Ju Lee; Anind K. Dey; Xuhai Xu (CHI, 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 (CHIL, 2024)

MisinfoEval: Generative AI in the Era of "Alternative Facts". - Saadia Gabriel; Liang Lyu; James Siderius; Marzyeh Ghassemi; Jacob Andreas; Asuman E. Ozdaglar (EMNLP, 2024)

Can AI Relate: Testing Large Language Model Response for Mental Health Support. - Saadia Gabriel; Isha Puri; Xuhai Xu; Matteo Malgaroli; Marzyeh Ghassemi (EMNLP (Findings), 2024)

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

Measuring Stochastic Data Complexity with Boltzmann Influence Functions. - Nathan H. Ng; Roger Baker Grosse; Marzyeh Ghassemi (ICML, 2024)

Position: Application-Driven Innovation in Machine Learning. - David Rolnick; Alán Aspuru-Guzik; Sara Beery; Bistra Dilkina; Priya L. Donti; Marzyeh Ghassemi; Hannah Kerner; Claire Monteleoni; Esther Rolf; Milind Tambe; Adam White (ICML, 2024)

Asymmetry in Low-Rank Adapters of Foundation Models. - Jiacheng Zhu; Kristjan H. Greenewald; Kimia Nadjahi; Haitz Sáez de Ocáriz Borde; Rickard Brüel Gabrielsson; Leshem Choshen; Marzyeh Ghassemi; Mikhail Yurochkin; Justin Solomon 001 (ICML, 2024)

FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging. - Kumail Alhamoud; Yasir Ghunaim; Motasem Alfarra; Thomas Hartvigsen; Philip Torr 001; Bernard Ghanem; Adel Bibi; Marzyeh Ghassemi (MICCAI (10), 2024)

Event-Based Contrastive Learning for Medical Time Series. - Nassim Oufattole; Hyewon Jeong; Matthew B. A. McDermott; Aparna Balagopalan; Bryan Jangeesingh; Marzyeh Ghassemi; Collin M. Stultz (MLHC, 2024)

MDAgents: An Adaptive Collaboration of LLMs for Medical Decision-Making. - Yubin Kim 002; Chanwoo Park; Hyewon Jeong; Yik Siu Chan; Xuhai Xu; Daniel McDuff; Hyeonhoon Lee; Marzyeh Ghassemi; Cynthia Breazeal; Hae Won Park 001 (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)

Improving Subgroup Robustness via Data Selection. - Saachi Jain; Kimia Hamidieh; Kristian Georgiev; Andrew Ilyas; Marzyeh Ghassemi; Aleksander Madry (NeurIPS, 2024)

Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study. - 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; et al. (CoRR, 2024)

Improving Black-box Robustness with In-Context Rewriting. - Kyle O'Brien; Nathan Ng 001; Isha Puri; Jorge Mendez; Hamid Palangi; Yoon Kim; Marzyeh Ghassemi; Thomas Hartvigsen (CoRR, 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)

Application-Driven Innovation in Machine Learning. - David Rolnick; Alán Aspuru-Guzik; Sara Beery; Bistra Dilkina; Priya L. Donti; Marzyeh Ghassemi; Hannah Kerner; Claire Monteleoni; Esther Rolf; Milind Tambe; Adam White (CoRR, 2024)

Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection. - Saachi Jain; Kimia Hamidieh; Kristian Georgiev; Andrew Ilyas; Marzyeh Ghassemi; Aleksander Madry (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)

Outlining the Borders for LLM Applications in Patient Education: Developing an Expert-in-the-Loop LLM-Powered Chatbot for Prostate Cancer Patient Education. - Yuexing Hao; Jason Holmes; Mark R. Waddle; Nathan Yu; Kirstin Vickers; Heather Preston; Drew Margolin; Corinna E. Löckenhoff; Aditya Vashistha; Marzyeh Ghassemi; Saleh Kalantari; Wei Liu (CoRR, 2024)

SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe. - Yuxin Xiao; Shujian Zhang; Wenxuan Zhou; Marzyeh Ghassemi; Sanqiang Zhao (CoRR, 2024)

MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious Correlations. - Qixuan Jin; Walter Gerych; Marzyeh Ghassemi (CoRR, 2024)

Generative AI in Medicine. - Divya Shanmugam; Monica Agrawal; Rajiv Movva; Irene Y. Chen; Marzyeh Ghassemi; Maia Jacobs; Emma Pierson (CoRR, 2024)

Large language models in biomedicine and health: current research landscape and future directions. - Zhiyong Lu; Yifan Peng 002; Trevor Cohen; Marzyeh Ghassemi; Chunhua Weng; Shubo Tian (J. Am. Medical Informatics Assoc., 2024)

Improving Black-box Robustness with In-Context Rewriting. - Kyle O'Brien; Nathan Hoyen Ng; Isha Puri; Jorge Mendez-Mendez; Hamid Palangi; Yoon Kim; Marzyeh Ghassemi; Thomas Hartvigsen (Trans. Mach. Learn. Res., 2024)

Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data. - Xuhai Xu; Bingsheng Yao; Yuanzhe Dong; Saadia Gabriel; Hong Yu 001; James A. Hendler; Marzyeh Ghassemi; Anind K. Dey; Dakuo Wang (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2024)

Using labels to limit AI misuse in health. - Elaine O. Nsoesie; Marzyeh Ghassemi (Nat. Comput. Sci., 2024)

A Study of Artifacts on Melanoma Classification under Diffusion-Based Perturbations. - Qixuan Jin; Marzyeh Ghassemi (CHIL, 2025)

Vision-Language Models Do Not Understand Negation. - Kumail Alhamoud; Shaden Alshammari; Yonglong Tian; Guohao Li 013; Philip H. S. Torr; Yoon Kim; Marzyeh Ghassemi (CVPR, 2025)

Lost in Transplantation: Characterizing Racial Gaps in Physician Organ Offer Acceptance. - Hammaad Adam; Rene S. Bermea; Ming-Ying Yang; Leo Anthony Celi; Marzyeh Ghassemi (FAccT, 2025)

Bias Delayed is Bias Denied? Assessing the Effect of Reporting Delays on Disparity Assessments. - Jennah Gosciak; Aparna Balagopalan; Derek Ouyang; Allison Koenecke; Marzyeh Ghassemi; Daniel E. Ho (FAccT, 2025)

The Medium is the Message: How Non-Clinical Information Shapes Clinical Decisions in LLMs. - Abinitha Gourabathina; Walter Gerych; Eileen Pan; Marzyeh Ghassemi (FAccT, 2025)

What's in a Query: Polarity-Aware Distribution-Based Fair Ranking. - Aparna Balagopalan; Kai Wang 071; Olawale Salaudeen; Asia Biega; Marzyeh Ghassemi (WWW, 2025)

Large language model integrations in cancer decision-making: a systematic review and meta-analysis. - Yuexing Hao; Zhiwen Qiu; Jason Holmes; Corinna E. Löckenhoff; Wei Liu; Marzyeh Ghassemi; Saleh Kalantari (npj Digit. Medicine, 2025)

Vision-Language Models Do Not Understand Negation. - Kumail Alhamoud; Shaden Alshammari; Yonglong Tian; Guohao Li 001; Philip Torr 001; Yoon Kim; Marzyeh Ghassemi (CoRR, 2025)

Speak Easy: Eliciting Harmful Jailbreaks from LLMs with Simple Interactions. - Yik Siu Chan; Narutatsu Ri; Yuxin Xiao; Marzyeh Ghassemi (CoRR, 2025)

MOSAIC: Modeling Social AI for Content Dissemination and Regulation in Multi-Agent Simulations. - Genglin Liu; Salman Rahman; Elisa Kreiss; Marzyeh Ghassemi; Saadia Gabriel (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)

When Style Breaks Safety: Defending Language Models Against Superficial Style Alignment. - Yuxin Xiao; Sana Tonekaboni; Walter Gerych; Vinith M. Suriyakumar; Marzyeh Ghassemi (CoRR, 2025)

KScope: A Framework for Characterizing the Knowledge Status of Language Models. - Yuxin Xiao; Shan Chen 004; Jack Gallifant; Danielle S. Bitterman; Thomas Hartvigsen; Marzyeh Ghassemi (CoRR, 2025)

Tiered Agentic Oversight: A Hierarchical Multi-Agent System for AI Safety in Healthcare. - Yubin Kim 002; Hyewon Jeong; Chanwoo Park; Eugene Park; Haipeng Zhang; Xin Liu 034; Hyeonhoon Lee; Daniel McDuff; Marzyeh Ghassemi; Cynthia Breazeal; Samir Tulebaev; Hae Won Park 001 (CoRR, 2025)

The MedPerturb Dataset: What Non-Content Perturbations Reveal About Human and Clinical LLM Decision Making. - Abinitha Gourabathina; Yuexing Hao; Walter Gerych; Marzyeh Ghassemi (CoRR, 2025)

Train Long, Think Short: Curriculum Learning for Efficient Reasoning. - Hasan Abed Al Kader Hammoud; Kumail Alhamoud; Abed Hammoud; Elie Bou-Zeid; Marzyeh Ghassemi; Bernard Ghanem (CoRR, 2025)