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Adarsh Subbaswamy
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The clinician and dataset shift in artificial intelligence
SG Finlayson, A Subbaswamy, K Singh, J Bowers, A Kupke, J Zittrain, ...
The New England Journal of Medicine, 283-286, 2021
3642021
Non-intrusive occupancy monitoring using smart meters
D Chen, S Barker, A Subbaswamy, D Irwin, P Shenoy
Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient …, 2013
2402013
From development to deployment: dataset shift, causality, and shift-stable models in health AI
A Subbaswamy, S Saria
Biostatistics 21 (2), 345-352, 2020
2012020
Preventing failures due to dataset shift: Learning predictive models that transport
A Subbaswamy, P Schulam, S Saria
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
1692019
Evaluating model robustness and stability to dataset shift
A Subbaswamy, R Adams, S Saria
International conference on artificial intelligence and statistics, 2611-2619, 2021
902021
Counterfactual normalization: Proactively addressing dataset shift and improving reliability using causal mechanisms
A Subbaswamy, S Saria
arXiv preprint arXiv:1808.03253, 2018
78*2018
Tutorial: safe and reliable machine learning
S Saria, A Subbaswamy
arXiv preprint arXiv:1904.07204, 2019
762019
Treatment-response models for counterfactual reasoning with continuous-time, continuous-valued interventions
H Soleimani, A Subbaswamy, S Saria
Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, 2017
622017
A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models
HE Wang, M Landers, R Adams, A Subbaswamy, H Kharrazi, DJ Gaskin, ...
Journal of the American Medical Informatics Association 29 (8), 1323-1333, 2022
312022
A unifying causal framework for analyzing dataset shift-stable learning algorithms
A Subbaswamy, B Chen, S Saria
Journal of Causal Inference 10 (1), 64-89, 2022
30*2022
I-spec: An end-to-end framework for learning transportable, shift-stable models
A Subbaswamy, S Saria
arXiv preprint arXiv:2002.08948, 2020
132020
Machine learning for health (ml4h) 2022
A Parziale, M Agrawal, S Tang, K Severson, L Oala, A Subbaswamy, ...
Machine Learning for Health, 1-11, 2022
22022
Towards a Post-Market Monitoring Framework for Machine Learning-based Medical Devices: A case study
J Feng, A Subbaswamy, A Gossmann, H Singh, B Sahiner, MO Kim, ...
arXiv preprint arXiv:2311.11463, 2023
12023
A hierarchical decomposition for explaining ML performance discrepancies
J Feng, H Singh, F Xia, A Subbaswamy, A Gossmann
arXiv preprint arXiv:2402.14254, 2024
2024
Causal Modeling for Training and Evaluating Dataset Shift-Stable Machine Learning Models in Healthcare
A Subbaswamy
Johns Hopkins University, 2023
2023
Machine Learning for Health symposium 2022--Extended Abstract track
A Parziale, M Agrawal, S Joshi, IY Chen, S Tang, L Oala, A Subbaswamy
arXiv preprint arXiv:2211.15564, 2022
2022
A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models (May, 10.1093/jamia/ocac065, 2022)
H Wang, M Landers, R Adams, A Subbaswamy, H Kharrazi, DJ Gaskin, ...
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 29 (9), 1656-1656, 2022
2022
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