Marzyeh Ghassemi
Orcid: 0000-0001-6349-7251
According to our database1,
Marzyeh Ghassemi
authored at least 104 papers
between 2013 and 2024.
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Bibliography
2024
Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., March, 2024
Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention.
CoRR, 2024
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.
CoRR, 2024
Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study.
CoRR, 2024
2023
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols.
Nat. Mac. Intell., August, 2023
Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning.
Trans. Mach. Learn. Res., 2023
VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception.
CoRR, 2023
VisAlign: Dataset for Measuring the Alignment between AI and Humans in Visual Perception.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Machine Learning for Healthcare Conference, 2023
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023
Clinical Relevance Score for Guided Trauma Injury Pattern Discovery with Weakly Supervised β-VAE.
Proceedings of the Conference on Health, Inference, and Learning, 2023
Proceedings of the Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 2023
Evaluating the Impact of Social Determinants on Health Prediction in the Intensive Care Unit.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023
2022
Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum.
npj Digit. Medicine, 2022
Decision-centered design of a clinical decision support system for acute management of pediatric congenital heart disease.
Frontiers Digit. Health, 2022
CoRR, 2022
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022
Proceedings of the Conference on Health, Inference, and Learning, 2022
Proceedings of the Conference on Health, Inference, and Learning, 2022
Proceedings of the Conference on Health, Inference, and Learning, 2022
Get To The Point! Problem-Based Curated Data Views To Augment Care For Critically Ill Patients.
Proceedings of the CHI '22: CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April 2022, 2022
Write It Like You See It: Detectable Differences in Clinical Notes by Race Lead to Differential Model Recommendations.
Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022
2021
npj Digit. Medicine, 2021
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations.
CoRR, 2021
Proceedings of the Biocomputing 2021: Proceedings of the Pacific Symposium, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021
Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021
Making Health AI Work in the Real World: Strategies, innovations, and best practices for using AI to improve care delivery.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
2020
CoRR, 2020
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data.
CoRR, 2020
Proceedings of the Machine Learning for Health Workshop, 2020
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare.
Proceedings of the Machine Learning for Health Workshop, 2020
Proceedings of the Machine Learning for Healthcare Conference, 2020
CheXpert++: Approximating the CheXpert Labeler for Speed, Differentiability, and Probabilistic Output.
Proceedings of the Machine Learning for Healthcare Conference, 2020
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020
MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020
Proceedings of the 3rd Clinical Natural Language Processing Workshop, 2020
2019
Modeling the Biological Pathology Continuum with HSIC-regularized Wasserstein Auto-encoders.
CoRR, 2019
The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Machine Learning for Health Workshop, 2019
Proceedings of the Machine Learning for Healthcare Conference, 2019
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks.
Proceedings of the Machine Learning for Healthcare Conference, 2019
Proceedings of the Machine Learning for Healthcare Conference, 2019
Proceedings of the Reproducibility in Machine Learning, 2019
2018
Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation.
CoRR, 2018
CoRR, 2018
Proceedings of the Machine Learning for Healthcare Conference, 2018
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
Representation learning in multi-dimensional clinical timeseries for risk and event prediction.
PhD thesis, 2017
Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database.
J. Am. Medical Informatics Assoc., 2017
CoRR, 2017
Proceedings of the Machine Learning for Health Care Conference, 2017
Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach.
Proceedings of the Machine Learning for Health Care Conference, 2017
Proceedings of the Summit on Clinical Research Informatics, 2017
2016
Proceedings of the 1st Machine Learning in Health Care, 2016
Prediction using patient comparison vs. modeling: A case study for mortality prediction.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016
2015
Corrections to "Learning to Detect Vocal Hyperfunction From Ambulatory Neck-Surface Acceleration Features: Initial Results For Vocal Fold Nodules".
IEEE Trans. Biomed. Eng., 2015
A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
2014
Learning to Detect Vocal Hyperfunction From Ambulatory Neck-Surface Acceleration Features: Initial Results for Vocal Fold Nodules.
IEEE Trans. Biomed. Eng., 2014
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014
2013
Probabilistically Populated Medical Record Templates: Reducing Clinical Documentation Time Using Patient Cooperation.
Proceedings of the AMIA 2013, 2013