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ORCIDMarzyeh Ghassemi
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- affiliation: Massachusetts Institute of Technology, USA
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2020 – today
- 2024
[j13]Xuhai Xu
, Bingsheng Yao, Yuanzhe Dong, Saadia Gabriel, Hong Yu, James A. Hendler, Marzyeh Ghassemi, Anind K. Dey, Dakuo Wang:
Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 8(1): 31:1-31:32 (2024)- [j12]Zhiyong Lu, Yifan Peng, Trevor Cohen, Marzyeh Ghassemi, Chunhua Weng, Shubo Tian:
Large language models in biomedicine and health: current research landscape and future directions. J. Am. Medical Informatics Assoc. 31(9): 1801-1811 (2024) - [c62]Adiba Orzikulova, Han Xiao, Zhipeng Li, Yukang Yan, Yuntao Wang, Yuanchun Shi, Marzyeh Ghassemi, Sung-Ju Lee, Anind K. Dey, Xuhai Xu:
Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention. CHI 2024: 250:1-250:20 - [c61]Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan, Marzyeh Ghassemi:
Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation. ICLR 2024 - [c60]Nathan H. Ng, Roger Baker Grosse, Marzyeh Ghassemi:
Measuring Stochastic Data Complexity with Boltzmann Influence Functions. ICML 2024 - [c59]David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White:
Position: Application-Driven Innovation in Machine Learning. ICML 2024 - [c58]Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon:
Asymmetry in Low-Rank Adapters of Foundation Models. ICML 2024 - [i73]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, David A. Sontag:
Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study. CoRR abs/2401.09637 (2024) - [i72]Kyle O'Brien, Nathan Ng, Isha Puri, Jorge Mendez, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi, Thomas Hartvigsen:
Improving Black-box Robustness with In-Context Rewriting. CoRR abs/2402.08225 (2024) - [i71]Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon:
Asymmetry in Low-Rank Adapters of Foundation Models. CoRR abs/2402.16842 (2024) - [i70]Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo:
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR abs/2403.01628 (2024) - [i69]Adiba Orzikulova, Han Xiao, Zhipeng Li, Yukang Yan, Yuntao Wang, Yuanchun Shi, Marzyeh Ghassemi, Sung-Ju Lee, Anind K. Dey, Xuhai Orson Xu:
Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention. CoRR abs/2403.05584 (2024) - [i68]David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White:
Application-Driven Innovation in Machine Learning. CoRR abs/2403.17381 (2024) - [i67]Saadia Gabriel, Isha Puri, Xuhai Xu, Matteo Malgaroli, Marzyeh Ghassemi:
Can AI Relate: Testing Large Language Model Response for Mental Health Support. CoRR abs/2405.12021 (2024) - [i66]Nathan Ng, Roger B. Grosse, Marzyeh Ghassemi:
Measuring Stochastic Data Complexity with Boltzmann Influence Functions. CoRR abs/2406.02745 (2024) - [i65]Saachi Jain, Kimia Hamidieh, Kristian Georgiev, Andrew Ilyas, Marzyeh Ghassemi, Aleksander Madry:
Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection. CoRR abs/2406.16846 (2024) - [i64]Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan, Marzyeh Ghassemi:
Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation. CoRR abs/2406.18562 (2024) - [i63]Kumail Alhamoud, Yasir Ghunaim, Motasem Alfarra, Thomas Hartvigsen, Philip Torr, Bernard Ghanem, Adel Bibi, Marzyeh Ghassemi:
FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging. CoRR abs/2407.08822 (2024) - [i62]Haoran Zhang, Aparna Balagopalan, Nassim Oufattole, Hyewon Jeong, Yan Wu, Jiacheng Zhu, Marzyeh Ghassemi:
LEMoN: Label Error Detection using Multimodal Neighbors. CoRR abs/2407.18941 (2024) - 2023
- [j11]Paula Dhiman, Rebecca Whittle, Ben Van Calster, Marzyeh Ghassemi, Xiaoxuan Liu, Melissa D. McCradden, Karel G. M. Moons, Richard D. Riley, Gary S. Collins:
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols. Nat. Mac. Intell. 5(8): 816-817 (2023) - [j10]Taylor W. Killian, Sonali Parbhoo, Marzyeh Ghassemi:
Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j9]Nathan H. Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi:
Predicting Out-of-Domain Generalization with Neighborhood Invariance. Trans. Mach. Learn. Res. 2023 (2023) - [c57]Ming-Ying Yang, Gloria Hyun-Jung Kwak, Tom J. Pollard, Leo Anthony Celi, Marzyeh Ghassemi:
Evaluating the Impact of Social Determinants on Health Prediction in the Intensive Care Unit. AIES 2023: 333-350 - [c56]Anja Thieme, Aditya V. Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger:
Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward. CHI Extended Abstracts 2023: 512:1-512:4 - [c55]Qixuan Jin, Jacobien H. F. Oosterhoff, Yepeng Huang, Marzyeh Ghassemi, Gabriel A Brat:
Clinical Relevance Score for Guided Trauma Injury Pattern Discovery with Weakly Supervised β-VAE. CHIL 2023: 314-339 - [c54]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:
Taking Off with AI: Lessons from Aviation for Healthcare. EAAMO 2023: 4:1-4:14 - [c53]Yuxin Xiao, Shulammite Lim, Tom Joseph Pollard, Marzyeh Ghassemi:
In the Name of Fairness: Assessing the Bias in Clinical Record De-identification. FAccT 2023: 123-137 - [c52]Vinith Menon Suriyakumar, Marzyeh Ghassemi, Berk Ustun:
When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction. ICML 2023: 33209-33228 - [c51]Yuzhe Yang, Haoran Zhang, Dina Katabi, Marzyeh Ghassemi:
Change is Hard: A Closer Look at Subpopulation Shift. ICML 2023: 39584-39622 - [c50]Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi:
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. ICML 2023: 41550-41578 - [c49]Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi:
Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals. MLHC 2023: 321-342 - [c48]Tom Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi:
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors. NeurIPS 2023 - [c47]Jiyoung Lee, Seungho Kim, Seunghyun Won, Joonseok Lee, Marzyeh Ghassemi, James Thorne, Jaeseok Choi, O.-Kil Kwon, Edward Choi:
VisAlign: Dataset for Measuring the Alignment between AI and Humans in Visual Perception. NeurIPS 2023 - [i61]Taylor W. Killian, Sonali Parbhoo, Marzyeh Ghassemi:
Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning. CoRR abs/2301.05664 (2023) - [i60]Yuzhe Yang, Haoran Zhang, Dina Katabi, Marzyeh Ghassemi:
Change is Hard: A Closer Look at Subpopulation Shift. CoRR abs/2302.12254 (2023) - [i59]Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger B. Grosse, Alireza Makhzani:
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. CoRR abs/2303.06992 (2023) - [i58]Yuxin Xiao, Shulammite Lim, Tom Joseph Pollard, Marzyeh Ghassemi:
In the Name of Fairness: Assessing the Bias in Clinical Record De-identification. CoRR abs/2305.11348 (2023) - [i57]Ming-Ying Yang, Gloria Hyun-Jung Kwak, Tom J. Pollard, Leo Anthony Celi, Marzyeh Ghassemi:
Evaluating the Impact of Social Determinants on Health Prediction. CoRR abs/2305.12622 (2023) - [i56]Jiyoung Lee, Seungho Kim, Seunghyun Won, Joonseok Lee, Marzyeh Ghassemi, James Thorne, Jaeseok Choi, O.-Kil Kwon, Edward Choi:
VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception. CoRR abs/2308.01525 (2023) - [i55]Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi:
Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals. CoRR abs/2308.04650 (2023) - [i54]Yuzhe Yang, Haoran Zhang, Judy W. Gichoya, Dina Katabi, Marzyeh Ghassemi:
The Limits of Fair Medical Imaging AI In The Wild. CoRR abs/2312.10083 (2023) - [i53]Hyewon Jeong, Nassim Oufattole, Aparna Balagopalan, Matthew B. A. McDermott, Payal Chandak, Marzyeh Ghassemi, Collin M. Stultz:
Event-Based Contrastive Learning for Medical Time Series. CoRR abs/2312.10308 (2023) - 2022
- [j8]Azadeh Assadi, Peter C. Laussen, Gabrielle Freire, Marzyeh Ghassemi, Patricia Trbovich:
Decision-centered design of a clinical decision support system for acute management of pediatric congenital heart disease. Frontiers Digit. Health 4 (2022) - [j7]Marzyeh Ghassemi, Shakir Mohamed:
Machine learning and health need better values. npj Digit. Medicine 5 (2022) - [j6]Sarah M. Goodday, E. Karlin, A. Brooks, C. Chapman, Daniel R. Karlin, Luca Foschini, E. Kipping, M. Wildman, M. Francis, H. Greenman, Li Li, Eric E. Schadt, Marzyeh Ghassemi, Anna Goldenberg, Francesca Cormack, Nick Taptiklis, Corey Centen, S. Smith, Stephen H. Friend:
Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum. npj Digit. Medicine 5 (2022) - [j5]Marzyeh Ghassemi, Elaine O. Nsoesie:
In medicine, how do we machine learn anything real? Patterns 3(1): 100392 (2022) - [c46]Hammaad Adam, Ming-Ying Yang, Kenrick Cato, Ioana Baldini, Charles Senteio, Leo Anthony Celi, Jiaming Zeng, Moninder Singh, Marzyeh Ghassemi:
Write It Like You See It: Detectable Differences in Clinical Notes by Race Lead to Differential Model Recommendations. AIES 2022: 7-21 - [c45]Minfan Zhang, Daniel Ehrmann, Mjaye Mazwi, Danny Eytan, Marzyeh Ghassemi, Fanny Chevalier:
Get To The Point! Problem-Based Curated Data Views To Augment Care For Critically Ill Patients. CHI 2022: 278:1-278:13 - [c44]Taylor W. Killian, Marzyeh Ghassemi, Shalmali Joshi:
Counterfactually Guided Policy Transfer in Clinical Settings. CHIL 2022: 5-31 - [c43]Mehdi Fatemi, Mary Wu, Jeremy Petch, Walter Nelson, Stuart J. Connolly, Alexander Benz, Anthony Carnicelli, Marzyeh Ghassemi:
Semi-Markov Offline Reinforcement Learning for Healthcare. CHIL 2022: 119-137 - [c42]Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Pfohl, Marzyeh Ghassemi:
Improving the Fairness of Chest X-ray Classifiers. CHIL 2022: 204-233 - [c41]Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg:
Uniform Priors for Data-Efficient Learning. CVPR Workshops 2022: 4016-4027 - [c40]Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh Ghassemi:
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations. FAccT 2022: 1194-1206 - [c39]Jimmy Ba, Murat A. Erdogdu, Marzyeh Ghassemi, Shengyang Sun, Taiji Suzuki, Denny Wu, Tianzong Zhang:
Understanding the Variance Collapse of SVGD in High Dimensions. ICLR 2022 - [c38]Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani:
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. ICLR 2022 - [c37]Natalie Dullerud, Karsten Roth, Kimia Hamidieh, Nicolas Papernot, Marzyeh Ghassemi:
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning. ICLR 2022 - [c36]Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B. Grosse:
If Influence Functions are the Answer, Then What is the Question? NeurIPS 2022 - [i52]Mehdi Fatemi, Mary Wu, Jeremy Petch, Walter Nelson, Stuart J. Connolly, Alexander Benz, Anthony Carnicelli, Marzyeh Ghassemi:
Semi-Markov Offline Reinforcement Learning for Healthcare. CoRR abs/2203.09365 (2022) - [i51]Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Robert Pfohl, Marzyeh Ghassemi:
Improving the Fairness of Chest X-ray Classifiers. CoRR abs/2203.12609 (2022) - [i50]Natalie Dullerud, Karsten Roth, Kimia Hamidieh, Nicolas Papernot, Marzyeh Ghassemi:
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning. CoRR abs/2203.12748 (2022) - [i49]Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh Ghassemi:
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations. CoRR abs/2205.03295 (2022) - [i48]Hammaad Adam, Ming-Ying Yang, Kenrick Cato, Ioana Baldini, Charles Senteio, Leo Anthony Celi, Jiaming Zeng, Moninder Singh, Marzyeh Ghassemi:
Write It Like You See It: Detectable Differences in Clinical Notes By Race Lead To Differential Model Recommendations. CoRR abs/2205.03931 (2022) - [i47]Vinith M. Suriyakumar, Marzyeh Ghassemi, Berk Ustun:
When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction. CoRR abs/2206.02058 (2022) - [i46]Nathan Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi:
Predicting Out-of-Domain Generalization with Local Manifold Smoothness. CoRR abs/2207.02093 (2022) - [i45]Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B. Grosse:
If Influence Functions are the Answer, Then What is the Question? CoRR abs/2209.05364 (2022) - [i44]Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi:
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. CoRR abs/2210.10769 (2022) - [i43]Thomas Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi:
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors. CoRR abs/2211.11031 (2022) - 2021
- [j4]Susanne Gaube, Harini Suresh, Martina Raue, Alexander Merritt, Seth J. Berkowitz, Eva Lermer, Joseph F. Coughlin, John V. Guttag, Errol Colak, Marzyeh Ghassemi:
Do as AI say: susceptibility in deployment of clinical decision-aids. npj Digit. Medicine 4 (2021) - [c35]Suchi Saria, Marzyeh Ghassemi, Ziad Obermeyer, Karandeep Singh, Pei-Yun S. Hsueh, Eric J. Topol:
Making Health AI Work in the Real World: Strategies, innovations, and best practices for using AI to improve care delivery. AMIA 2021 - [c34]Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi:
A comprehensive EHR timeseries pre-training benchmark. CHIL 2021: 257-278 - [c33]Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi:
An empirical framework for domain generalization in clinical settings. CHIL 2021: 279-290 - [c32]Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi:
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. CIKM 2021: 606-616 - [c31]Victoria Cheng, Vinith M. Suriyakumar, Natalie Dullerud, Shalmali Joshi, Marzyeh Ghassemi:
Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness. FAccT 2021: 149-160 - [c30]Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi:
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. FAccT 2021: 723-734 - [c29]Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi:
Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. ICML 2021: 9095-9106 - [c28]Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi:
Learning Optimal Predictive Checklists. NeurIPS 2021: 1215-1229 - [c27]Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi:
Medical Dead-ends and Learning to Identify High-Risk States and Treatments. NeurIPS 2021: 4856-4870 - [c26]Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer:
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. NeurIPS 2021: 25006-25018 - [c25]Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew B. A. McDermott, Irene Y. Chen, Marzyeh Ghassemi:
CheXclusion: Fairness gaps in deep chest X-ray classifiers. PSB 2021 - [e2]Marzyeh Ghassemi, Tristan Naumann, Emma Pierson:
ACM CHIL '21: ACM Conference on Health, Inference, and Learning, Virtual Event, USA, April 8-9, 2021. ACM 2021, ISBN 978-1-4503-8359-2 [contents] - [i42]Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi:
An Empirical Framework for Domain Generalization in Clinical Settings. CoRR abs/2103.11163 (2021) - [i41]Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer:
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. CoRR abs/2107.09562 (2021) - [i40]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, Brandon J. Price, Saptarshi Purkayastha, Ayis Pyrros, Luke Oakden-Rayner, Chima Okechukwu, Laleh Seyyed-Kalantari, Hari Trivedi, Ryan Wang, Zachary Zaiman, Haoran Zhang, Judy W. Gichoya:
Reading Race: AI Recognises Patient's Racial Identity In Medical Images. CoRR abs/2107.10356 (2021) - [i39]Stephen R. Pfohl, Haoran Zhang, Yizhe Xu, Agata Foryciarz, Marzyeh Ghassemi, Nigam H. Shah:
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations. CoRR abs/2108.12250 (2021) - [i38]Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi:
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. CoRR abs/2108.12510 (2021) - [i37]Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi:
Medical Dead-ends and Learning to Identify High-risk States and Treatments. CoRR abs/2110.04186 (2021) - [i36]Zining Zhu, Aparna Balagopalan, Marzyeh Ghassemi, Frank Rudzicz:
Quantifying the Task-Specific Information in Text-Based Classifications. CoRR abs/2110.08931 (2021) - [i35]Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi:
Learning Optimal Predictive Checklists. CoRR abs/2112.01020 (2021) - 2020
- [c24]Alister D. Costa, Stefan Denkovski, Michal Malyska, Sae Young Moon, Brandon Rufino, Zhen Yang, Taylor W. Killian, Marzyeh Ghassemi:
Multiple Sclerosis Severity Classification From Clinical Text. ClinicalNLP@EMNLP 2020: 7-23 - [c23]Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi:
Hurtful words: quantifying biases in clinical contextual word embeddings. CHIL 2020: 110-120 - [c22]Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan, Marzyeh Ghassemi, Michael C. Hughes, Tristan Naumann:
MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III. CHIL 2020: 222-235 - [c21]Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi:
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness. EMNLP (1) 2020: 1268-1283 - [c20]Matthew B. A. McDermott, Tzu-Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits:
CheXpert++: Approximating the CheXpert Labeler for Speed, Differentiability, and Probabilistic Output. MLHC 2020: 913-927 - [c19]Bret Nestor, Liam G. McCoy, Amol Verma, Chloé Pou-Prom, Joshua Murray, Sebnem Kuzulugil, David Dai, Muhammad Mamdani, Anna Goldenberg, Marzyeh Ghassemi:
Preparing a Clinical Support Model for Silent Mode in General Internal Medicine. MLHC 2020: 950-972 - [c18]Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi:
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare. ML4H@NeurIPS 2020: 139-160 - [c17]Shirly Wang, Seung Eun Yi, Shalmali Joshi, Marzyeh Ghassemi:
Confounding Feature Acquisition for Causal Effect Estimation. ML4H@NeurIPS 2020: 379-396 - [e1]Marzyeh Ghassemi:
ACM CHIL '20: ACM Conference on Health, Inference, and Learning, Toronto, Ontario, Canada, April 2-4, 2020 [delayed]. ACM 2020, ISBN 978-1-4503-7046-2 [contents] - [i34]Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew B. A. McDermott, Marzyeh Ghassemi:
CheXclusion: Fairness gaps in deep chest X-ray classifiers. CoRR abs/2003.00827 (2020) - [i33]Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi:
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings. CoRR abs/2003.11515 (2020) - [i32]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:
Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning. CoRR abs/2005.11856 (2020) - [i31]Taylor W. Killian, Marzyeh Ghassemi, Shalmali Joshi:
Counterfactually Guided Policy Transfer in Clinical Settings. CoRR abs/2006.11654 (2020) - [i30]Joseph Paul Cohen, Paul Morrison, Lan Dao, Karsten Roth, Tim Q. Duong, Marzyeh Ghassemi:
COVID-19 Image Data Collection: Prospective Predictions Are the Future. CoRR abs/2006.11988 (2020) - [i29]Matthew B. A. McDermott, Tzu-Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits:
CheXpert++: Approximating the CheXpert labeler for Speed, Differentiability, and Probabilistic Output. CoRR abs/2006.15229 (2020) - [i28]Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi:
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data. CoRR abs/2007.10185 (2020) - [i27]Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi:
S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. CoRR abs/2009.08348 (2020) - [i26]Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi:
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness. CoRR abs/2009.10195 (2020) - [i25]Irene Y. Chen, Emma Pierson, Sherri Rose, Shalmali Joshi, Kadija Ferryman, Marzyeh Ghassemi:
Ethical Machine Learning in Health Care. CoRR abs/2009.10576 (2020) - [i24]Irene Y. Chen, Shalmali Joshi, Marzyeh Ghassemi, Rajesh Ranganath:
Probabilistic Machine Learning for Healthcare. CoRR abs/2009.11087 (2020) - [i23]Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi:
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