Publications

The medical algorithmic audit

Xiaoxuan Liu, Ben Glocker, Melissa M McCradden, Marzyeh Ghassemi, Alastair K Denniston, Lauren Oakden-Rayner
2022 The Lancet Digital Health

Semi-Markov Offline Reinforcement Learning for Healthcare

Mehdi Fatemi, Mary Wu, Jeremy Petch, Walter Nelson, Stuart J Connolly, Alexander Benz, Anthony Carnicelli, Marzyeh Ghassemi
2022 Conference on Health, Inference, and Learning

In medicine, how do we machine learn anything real?

Marzyeh Ghassemi, Elaine Okanyene Nsoesie
2022 Patterns
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Improving the Fairness of Chest X-ray Classifiers

Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Pfohl, Marzyeh Ghassemi
2022 Conference on Health, Inference, and Learning
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Counterfactually guided policy transfer in clinical settings

Taylor W Killian, Marzyeh Ghassemi, Shalmali Joshi
2022 Conference on Health, Inference, and Learning
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What every reader should know about studies using electronic health record data but may be afraid to ask

Isaac S Kohane, Bruce J Aronow, Paul Avillach, Brett K Beaulieu-Jones, Riccardo Bellazzi, Robert L Bradford, Gabriel A Brat, Mario Cannataro, James J Cimino, Noelia Garcia-Barrio, others
2021 Journal of medical Internet research

Visualization of deep models on nursing notes and physiological data for predicting health outcomes through temporal sliding windows

Jienan Yao, Yuyang Liu, Brenna Li, Stephen Gou, Chloe Pou-Prom, Joshua Murray, Amol Verma, Muhammad Mamdani, Marzyeh Ghassemi
2021 Explainable AI in Healthcare and Medicine

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

Laleh Seyyed-Kalantari, Haoran Zhang, Matthew McDermott, Irene Y Chen, Marzyeh Ghassemi
2021 Nature Medicine
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The role of machine learning in clinical research: transforming the future of evidence generation

E Hope Weissler, Tristan Naumann, Tomas Andersson, Rajesh Ranganath, Olivier Elemento, Yuan Luo, Daniel F Freitag, James Benoit, Michael C Hughes, Faisal Khan, others
2021 Trials

The false hope of current approaches to explainable artificial intelligence in health care

Marzyeh Ghassemi, Luke Oakden-Rayner, Andrew L Beam
2021 The Lancet Digital Health

Simultaneous Similarity-based Self-Distillation for Deep Metric Learning

Karsten Roth, Timo Milbich, Bjorn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi
2021 International Conference on Machine Learning

Reproducibility in machine learning for health research: Still a ways to go

Matthew BA McDermott, Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Luca Foschini, Marzyeh Ghassemi
2021 Science Translational Medicine

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, others
2021 arXiv preprint arXiv:2107.10356

Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing

Sindhu Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi
2021 arXiv preprint arXiv:2108.12510

Problems in the deployment of machine-learned models in health care

Joseph Paul Cohen, Tianshi Cao, Joseph D Viviano, Chin-Wei Huang, Michael Fralick, Marzyeh Ghassemi, Muhammad Mamdani, Russell Greiner, Yoshua Bengio
2021 CMAJ

Predicting hospitalizations related to ambulatory care sensitive conditions with machine learning for population health planning: derivation and validation cohort study

Seung Eun Yi, Vinyas Harish, Jahir M Gutierrez, Mathieu Ravaut, Kathy Kornas, Tristan Watson, Tomi Poutanen, Marzyeh Ghassemi, Maksims Volkovs, Laura Rosella
2021 medRxiv

Medical Dead-ends and Learning to Identify High-risk States and Treatments

Mehdi Fatemi, Taylor W Killian, Jayakumar Subramanian, Marzyeh Ghassemi
2021 Advances in Neural Information Processing Systems
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Learning Optimal Predictive Checklists

Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi
2021 Advances in Neural Information Processing Systems
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Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning

Natalie Dullerud, Karsten Roth, Kimia Hamidieh, Nicolas Papernot, Marzyeh Ghassemi
2021 International Conference on Learning Representations
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Implementing machine learning in medicine

Amol A Verma, Joshua Murray, Russell Greiner, Joseph Paul Cohen, Kaveh G Shojania, Marzyeh Ghassemi, Sharon E Straus, Chloe Pou-Prom, Muhammad Mamdani
2021 CMAJ

Five principles for the intelligent use of AI in medical imaging

Errol Colak, Robert Moreland, Marzyeh Ghassemi
2021 Springer

Equity in essence: a call for operationalising fairness in machine learning for healthcare

Judy Wawira Gichoya, Liam G McCoy, Leo Anthony Celi, Marzyeh Ghassemi
2021 BMJ Health & Care Informatics

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
2021 NPJ digital medicine

Dear Watch, Should I Get a COVID-19 Test? Designing deployable machine learning for wearables

Bret Nestor, Jaryd Hunter, Raghu Kainkaryam, Erik Drysdale, Jeffrey B Inglis, Allison Shapiro, Sujay Nagaraj, Marzyeh Ghassemi, Luca Foschini, Anna Goldenberg
2021 medRxiv

Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings

Vinith M Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi
2021 Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning

Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Bjorn Ommer
2021 arXiv preprint arXiv:2107.09562

Characteristics and outcomes of hospital admissions for COVID-19 and influenza in the Toronto area

Amol A Verma, Tejasvi Hora, Hae Young Jung, Michael Fralick, Sarah L Malecki, Lauren Lapointe-Shaw, Adina Weinerman, Terence Tang, Janice L Kwan, Jessica J Liu, others
2021 CMAJ

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
2021 Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

An empirical framework for domain generalization in clinical settings

Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi
2021 Proceedings of the Conference on Health, Inference, and Learning

A comparison of approaches to improve worst-case predictive model performance over patient subpopulations

Stephen R Pfohl, Haoran Zhang, Yizhe Xu, Agata Foryciarz, Marzyeh Ghassemi, Nigam H Shah
2021 arXiv preprint arXiv:2108.12250

Uniform Priors for Data-Efficient Transfer

Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Hugo Larochelle, Animesh Garg
2020 arXiv preprint arXiv:2006.16524

Treating health disparities with artificial intelligence

Irene Y Chen, Shalmali Joshi, Marzyeh Ghassemi
2020 Nature medicine

Ssmba: Self-supervised manifold based data augmentation for improving out-of-domain robustness

Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi
2020 arXiv preprint arXiv:2009.10195

Self-supervised contrastive learning of protein representations by mutual information maximization

Amy X Lu, Haoran Zhang, Marzyeh Ghassemi, Alan M Moses
2020 BioRxiv

S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning

Karsten Roth, Timo Milbich, Bjorn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi
2020 arXiv preprint arXiv:2009.08348

Probabilistic machine learning for healthcare

Irene Y Chen, Shalmali Joshi, Marzyeh Ghassemi, Rajesh Ranganath
2020 Annual Review of Biomedical Data Science

Preparing a Clinical Support Model for Silent Mode in General Internal Medicine

Bret Nestor, Liam G McCoy, Amol Verma, Chloe Pou-Prom, Joshua Murray, Sebnem Kuzulugil, David Dai, Muhammad Mamdani, Anna Goldenberg, Marzyeh Ghassemi
2020 Machine Learning for Healthcare Conference

Predicting covid-19 pneumonia severity on chest x-ray with deep learning

Joseph Paul Cohen, Lan Dao, Karsten Roth, Paul Morrison, Yoshua Bengio, Almas F Abbasi, Beiyi Shen, Hoshmand Kochi Mahsa, Marzyeh Ghassemi, Haifang Li, others
2020 Cureus

Patient characteristics, clinical care, resource use, and outcomes associated with hospitalization for COVID-19 in the Toronto area

Amol Verma, Tejasvi Hora, Hae Young Jung, Michael Fralick, Sarah Malecki, Lauren Lapointe-Shaw, Adina Weinerman, Terence Tang, Janice Kwan, Jessica J Liu, others
2020 medRxiv

Multiple sclerosis severity classification from clinical text

Alister D Costa, Stefan Denkovski, Michal Malyska, Sae Young Moon, Brandon Rufino, Zhen Yang, Taylor Killian, Marzyeh Ghassemi
2020 arXiv preprint arXiv:2010.15316

Mimic-extract: A data extraction, preprocessing, and representation pipeline for mimic-iii

Shirly Wang, Matthew BA McDermott, Geeticka Chauhan, Marzyeh Ghassemi, Michael C Hughes, Tristan Naumann
2020 Proceedings of the ACM Conference on Health, Inference, and Learning

Improving Dialogue Breakdown Detection with Semi-Supervised Learning

Nathan Ng, Marzyeh Ghassemi, Narendran Thangarajan, Jiacheng Pan, Qi Guo
2020 arXiv preprint arXiv:2011.00136

Hurtful words: quantifying biases in clinical contextual word embeddings

Haoran Zhang, Amy X Lu, Mohamed Abdalla, Matthew McDermott, Marzyeh Ghassemi
2020 proceedings of the ACM Conference on Health, Inference, and Learning

Ethical Machine Learning in Healthcare

Irene Y Chen, Emma Pierson, Sherri Rose, Shalmali Joshi, Kadija Ferryman, Marzyeh Ghassemi
2020 Annual Review of Biomedical Data Science

Ensuring machine learning for healthcare works for all

Liam G McCoy, John D Banja, Marzyeh Ghassemi, Leo Anthony Celi
2020 BMJ Health & Care Informatics

Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation

Aparna Balagopalan, Jekaterina Novikova, Matthew BA Mcdermott, Bret Nestor, Tristan Naumann, Marzyeh Ghassemi
2020 Machine Learning for Health Workshop

Covid-19 image data collection: Prospective predictions are the future

Joseph Paul Cohen, Paul Morrison, Lan Dao, Karsten Roth, Tim Q Duong, Marzyeh Ghassemi
2020 arXiv preprint arXiv:2006.11988

Confounding Feature Acquisition for Causal Effect Estimation

Shirly Wang, Seung Eun Yi, Shalmali Joshi, Marzyeh Ghassemi
2020 Machine Learning for Health

Chexpert++: Approximating the chexpert labeler for speed, differentiability, and probabilistic output

Matthew BA McDermott, Tzu Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits
2020 Machine Learning for Healthcare Conference

CheXclusion: Fairness gaps in deep chest X-ray classifiers

Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew McDermott, Irene Y Chen, Marzyeh Ghassemi
2020 BIOCOMPUTING 2021: Proceedings of the Pacific Symposium

Challenges to the reproducibility of machine learning models in health care

Andrew L Beam, Arjun K Manrai, Marzyeh Ghassemi
2020 Jama

Challenges of Differentially Private Prediction in Healthcare Settings

Vinith M Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi
2020

Building a data science platform for better health

Laura C Rosella, Ajay Agrawal, Phillip Awadalla, Adalsteinn Brown, Jeffrey Brook, Lori Diemert, France Gagnon, Marzyeh Ghassemi, Avi Goldfarb, Rick Glazier, others
2020

An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare

Taylor Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi
2020 arXiv preprint arXiv:2011.11235

A review of challenges and opportunities in machine learning for health

Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L Beam, Irene Y Chen, Rajesh Ranganath
2020 AMIA Summits on Translational Science Proceedings

A comprehensive evaluation of multi-task learning and multi-task pre-training on EHR time-series data

Matthew McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
2020 arXiv preprint arXiv:2007.10185

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, Trishan Panch
2019 The Lancet Digital Health

Towards characterizing the high-dimensional bias of kernel-based particle inference algorithms

Jimmy Ba, Murat A Erdogdu, Marzyeh Ghassemi, Taiji Suzuki, Shengyang Sun, Denny Wu, Tianzong Zhang
2019

The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data

Leo A Celi, Luca Citi, Marzyeh Ghassemi, Tom J Pollard
2019 PloS one

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
2019 arXiv preprint arXiv:1906.07282

Reproducibility in machine learning for health

Matthew McDermott, Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Marzyeh Ghassemi, Luca Foschini
2019 arXiv preprint arXiv:1907.01463

Practical guidance on artificial intelligence for health-care data

Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L Beam, Irene Y Chen, Rajesh Ranganath
2019 The Lancet Digital Health

Modeling the biological pathology continuum with hsic-regularized wasserstein auto-encoders

Denny Wu, Hirofumi Kobayashi, Charles Ding, Lei Cheng, Keisuke Goda Marzyeh Ghassemi
2019 arXiv preprint arXiv:1901.06618

Feature robustness in non-stationary health records: caveats to deployable model performance in common clinical machine learning tasks

Bret Nestor, Matthew BA McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C Hughes, Anna Goldenberg, Marzyeh Ghassemi
2019 Machine Learning for Healthcare Conference

Do no harm: a roadmap for responsible machine learning for health care

Jenna Wiens, Suchi Saria, Mark Sendak, Marzyeh Ghassemi, Vincent X Liu, Finale Doshi-Velez, Kenneth Jung, Katherine Heller, David Kale, Mohammed Saeed, others
2019 Nature medicine

Clinically accurate chest x-ray report generation

Guanxiong Liu, Tzu-Ming Harry Hsu, Matthew McDermott, Willie Boag, Wei-Hung Weng, Peter Szolovits, Marzyeh Ghassemi
2019 Machine Learning for Healthcare Conference

Can AI help reduce disparities in general medical and mental health care?

Irene Y Chen, Peter Szolovits, Marzyeh Ghassemi
2019 AMA journal of ethics

Building a research partnership between computer scientists and health service researchers for access and analysis of population-level health datasets: what are we learning?

Michael Schull, Michael Brudno, Marzyeh Ghassemi, Garth Gibson, Anna Goldenbrg, Alison Paprica, Laura Rosella, Therese Stukel, Charles Victor, Carl Virtanen
2019 International Journal of Population Data Science

The effect of heterogeneous data for Alzheimer's disease detection from speech

Aparna Balagopalan, Jekaterina Novikova, Frank Rudzicz, Marzyeh Ghassemi
2018 arXiv preprint arXiv:1811.12254

Semi-supervised biomedical translation with cycle wasserstein regression GANs

Matthew McDermott, Tom Yan, Tristan Naumann, Nathan Hunt, Harini Suresh, Peter Szolovits, Marzyeh Ghassemi
2018 Proceedings of the AAAI Conference on Artificial Intelligence

Rethinking clinical prediction: why machine learning must consider year of care and feature aggregation

Bret Nestor, Matthew McDermott, Geeticka Chauhan, Tristan Naumann, Michael C Hughes, Anna Goldenberg, Marzyeh Ghassemi
2018 arXiv preprint arXiv:1811.12583

Racial disparities and mistrust in end-of-life care

Willie Boag, Harini Suresh, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi
2018 Machine Learning for Healthcare Conference

Opportunities in machine learning for healthcare

Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L Beam, Rajesh Ranganath
2018 arXiv preprint arXiv:1806.00388

Modeling mistrust in end-of-life care

Willie Boag, Harini Suresh, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi
2018 arXiv preprint arXiv:1807.00124

Machine learning for health (ML4H) workshop at NeurIPS 2018

Natalia Antropova, Andrew L Beam, Brett K Beaulieu-Jones, Irene Chen, Corey Chivers, Adrian Dalca, Sam Finlayson, Madalina Fiterau, Jason Alan Fries, Marzyeh Ghassemi, others
2018 arXiv preprint arXiv:1811.07216

Clinicalvis: Supporting clinical task-focused design evaluation

Marzyeh Ghassemi, Mahima Pushkarna, James Wexler, Jesse Johnson, Paul Varghese
2018 arXiv preprint arXiv:1810.05798

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
2017 Journal of the American Medical Informatics Association

The use of autoencoders for discovering patient phenotypes

Harini Suresh, Peter Szolovits, Marzyeh Ghassemi
2017 arXiv preprint arXiv:1703.07004

Representation learning in multi-dimensional clinical timeseries for risk and event prediction

Marzyeh Ghassemi
2017

Predicting intervention onset in the ICU with switching state space models

Marzyeh Ghassemi, Mike Wu, Michael C Hughes, Peter Szolovits, Finale Doshi-Velez
2017 AMIA Summits on Translational Science Proceedings

Learning Clinical Events

Marzyeh Ghassemi, Harini Suresh, Nathan Hunt, Tristan Naumann, Leo Anthony Celi, Peter Szolovits
2017

Deep reinforcement learning for sepsis treatment

Aniruddh Raghu, Matthieu Komorowski, Imran Ahmed, Leo Celi, Peter Szolovits, Marzyeh Ghassemi
2017 arXiv preprint arXiv:1711.09602

Continuous state-space models for optimal sepsis treatment: a deep reinforcement learning approach

Aniruddh Raghu, Matthieu Komorowski, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi
2017 Machine Learning for Healthcare Conference

Clinical intervention prediction and understanding with deep neural networks

Harini Suresh, Nathan Hunt, Alistair Johnson, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi
2017 Machine Learning for Healthcare Conference

Uncovering voice misuse using symbolic mismatch

Marzyeh Ghassemi, Zeeshan Syed, Daryush Mehta, Jarrad Van Stan, Robert Hillman, John Guttag
2016 Machine Learning for Healthcare Conference

Sodium modelling to reduce intradialytic hypotension during haemodialysis for acute kidney injury in the intensive care unit

Katherine E Lynch, Fatimah Ghassemi, Jennifer E Flythe, Mengling Feng, Marzyeh Ghassemi, Leo Anthony Celi, Steven M Brunelli
2016 Nephrology

Prediction using patient comparison vs. modeling: A case study for mortality prediction

Mark Hoogendoorn, Ali El Hassouni, Kwongyen Mok, Marzyeh Ghassemi, Peter Szolovits
2016 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

Predicting early psychiatric readmission with natural language processing of narrative discharge summaries

Anna Rumshisky, Marzyeh Ghassemi, Tristan Naumann, Peter Szolovits, VM Castro, TH McCoy, RH Perlis
2016 Translational psychiatry

Data Analysis

Jesse D Raffa, Marzyeh Ghassemi, Tristan Naumann, Mengling Feng, Douglas Hsu
2016 Secondary Analysis of Electronic Health Records

State of the art review: the data revolution in critical care

Marzyeh Ghassemi, Leo Anthony Celi, David J Stone
2015 Critical Care

Short-term mortality prediction for elderly patients using Medicare claims data

Maggie Makar, Marzyeh Ghassemi, David M Cutler, Ziad Obermeyer
2015 International journal of machine learning and computing

Metadata correction: making big data useful for health care: a summary of the inaugural mit critical data conference

Omar Badawi, Thomas Brennan, Leo Anthony Celi, Mengling Feng, Marzyeh Ghassemi, Andrea Ippolito, Alistair Johnson, Roger G Mark, Louis Mayaud, George Moody, others
2015 JMIR medical informatics

A multivariate timeseries modeling approach to severity of illness assessment and forecasting in ICU with sparse, heterogeneous clinical data

Marzyeh Ghassemi, Marco Pimentel, Tristan Naumann, Thomas Brennan, David Clifton, Peter Szolovits, Mengling Feng
2015 Proceedings of the AAAI conference on artificial intelligence

Unfolding physiological state: Mortality modelling in intensive care units

Marzyeh Ghassemi, Tristan Naumann, Finale Doshi-Velez, Nicole Brimmer, Rohit Joshi, Anna Rumshisky, Peter Szolovits
2014 Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining

Subglottal ambulatory monitoring of vocal function to improve voice disorder assessment

Robert E Hillman, Daryush Mehta, Jarrad H Van Stan, Matias Zanartu, Marzyeh Ghassemi, John V Guttag
2014 The Journal of the Acoustical Society of America

Making big data useful for health care: a summary of the inaugural mit critical data conference

Omar Badawi, Thomas Brennan, Leo Anthony Celi, Mengling Feng, Marzyeh Ghassemi, Andrea Ippolito, Alistair Johnson, Roger G Mark, Louis Mayaud, George Moody, others
2014 JMIR medical informatics

Leveraging a critical care database: selective serotonin reuptake inhibitor use prior to ICU admission is associated with increased hospital mortality

Marzyeh Ghassemi, John Marshall, Nakul Singh, David J Stone, Leo Anthony Celi
2014 Chest