Harini Suresh
Harini Suresh
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Cited by
Cited by
A framework for understanding sources of harm throughout the machine learning life cycle
H Suresh, J Guttag
Proceedings of the 1st ACM Conference on Equity and Access in Algorithms …, 2021
Underspecification presents challenges for credibility in modern machine learning
A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...
Journal of Machine Learning Research 23 (226), 1-61, 2022
Do as AI say: susceptibility in deployment of clinical decision-aids
S Gaube, H Suresh, M Raue, A Merritt, SJ Berkowitz, E Lermer, ...
NPJ digital medicine 4 (1), 31, 2021
Clinical intervention prediction and understanding with deep neural networks
H Suresh, N Hunt, A Johnson, LA Celi, P Szolovits, M Ghassemi
Machine learning for healthcare conference, 322-337, 2017
Beyond expertise and roles: A framework to characterize the stakeholders of interpretable machine learning and their needs
H Suresh, SR Gomez, KK Nam, A Satyanarayan
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021
Learning tasks for multitask learning: Heterogenous patient populations in the icu
H Suresh, JJ Gong, JV Guttag
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
Misplaced trust: Measuring the interference of machine learning in human decision-making
H Suresh, N Lao, I Liccardi
Proceedings of the 12th ACM Conference on Web Science, 315-324, 2020
Orientation-specific attachment of polymeric microtubes on cell surfaces
JB Gilbert, JS O'Brien, HS Suresh, RE Cohen, MF Rubner
WILEY-VCH Verlag GmbH & Co., 2013
Use of machine-learning algorithms to determine features of systolic blood pressure variability that predict poor outcomes in hypertensive patients
RC Lacson, B Baker, H Suresh, K Andriole, P Szolovits, E Lacson Jr
Clinical kidney journal 12 (2), 206-212, 2019
Towards intersectional feminist and participatory ML: a case study in supporting feminicide counterdata collection
H Suresh, R Movva, AL Dogan, R Bhargava, I Cruxen, A Martinez Cuba, ...
2022 ACM Conference on Fairness, Accountability, and Transparency, 667-678, 2022
Non-task expert physicians benefit from correct explainable AI advice when reviewing X-rays
S Gaube, H Suresh, M Raue, E Lermer, TK Koch, MFC Hudecek, ...
Scientific reports 13 (1), 1383, 2023
The use of autoencoders for discovering patient phenotypes
H Suresh, P Szolovits, M Ghassemi
arXiv preprint arXiv:1703.07004, 2017
Semi-supervised biomedical translation with cycle wasserstein regression GANs
M McDermott, T Yan, T Naumann, N Hunt, H Suresh, P Szolovits, ...
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
Intuitively assessing ml model reliability through example-based explanations and editing model inputs
H Suresh, KM Lewis, J Guttag, A Satyanarayan
Proceedings of the 27th International Conference on Intelligent User …, 2022
Tech worker organizing for power and accountability
W Boag, H Suresh, B Lepe, C D'Ignazio
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
Understanding potential sources of harm throughout the machine learning life cycle
H Suresh, J Guttag
MIT Schwarzman College of Computing, 2021
Racial disparities and mistrust in end-of-life care
W Boag, H Suresh, LA Celi, P Szolovits, M Ghassemi
Machine learning for healthcare conference, 587-602, 2018
Feminicide & machine learning: detecting gender-based violence to strengthen civil sector activism
C D’Ignazio, HS Val, S Fumega, H Suresh, I Cruxên
Feminicide and counterdata production: Activist efforts to monitor and challenge gender-related violence
C D'Ignazio, I Cruxên, HS Val, AM Cuba, M García-Montes, S Fumega, ...
Patterns 3 (7), 2022
Improved text classification via test-time augmentation
H Lu, D Shanmugam, H Suresh, J Guttag
arXiv preprint arXiv:2206.13607, 2022
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