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Roy Adams
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Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis
R Adams, KE Henry, A Sridharan, H Soleimani, A Zhan, N Rawat, ...
Nature medicine 28 (7), 1455-1460, 2022
1532022
Evaluating model robustness and stability to dataset shift
A Subbaswamy, R Adams, S Saria
International conference on artificial intelligence and statistics, 2611-2619, 2021
982021
Impact of a collective intelligence tailored messaging system on smoking cessation: the perspect randomized experiment
RS Sadasivam, EM Borglund, R Adams, BM Marlin, TK Houston
Journal of medical Internet research 18 (11), e285, 2016
652016
Factors driving provider adoption of the TREWS machine learning-based early warning system and its effects on sepsis treatment timing
KE Henry, R Adams, C Parent, H Soleimani, A Sridharan, L Johnson, ...
Nature Medicine, 1-8, 2022
612022
Deep phenotyping of Parkinson’s disease
E Dorsey, L Omberg, E Waddell, JL Adams, R Adams, MR Ali, K Amodeo, ...
Journal of Parkinson's Disease 10 (3), 855-873, 2020
512020
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
392022
rconverse: Moment by moment conversation detection using a mobile respiration sensor
R Bari, RJ Adams, MM Rahman, MB Parsons, EH Buder, S Kumar
Proceedings of the ACM on interactive, mobile, wearable and ubiquitous …, 2018
322018
Towards collaborative filtering recommender systems for tailored health communications
BM Marlin, RJ Adams, R Sadasivam, TK Houston
AMIA annual symposium proceedings 2013, 1600, 2013
23*2013
PERSPeCT: collaborative filtering for tailored health communications
RJ Adams, RS Sadasivam, K Balakrishnan, RL Kinney, TK Houston, ...
Proceedings of the 8th ACM Conference on Recommender systems, 329-332, 2014
212014
Hierarchical span-based conditional random fields for labeling and segmenting events in wearable sensor data streams
R Adams, N Saleheen, E Thomaz, A Parate, S Kumar, B Marlin
International conference on machine learning, 334-343, 2016
172016
Learning models from data with measurement error: Tackling underreporting
R Adams, Y Ji, X Wang, S Saria
International Conference on Machine Learning, 61-70, 2019
162019
Learning time series detection models from temporally imprecise labels
R Adams, B Marlin
Artificial Intelligence and Statistics, 157-165, 2017
122017
Endogenous and exogenous thyrotoxicosis and risk of incident cognitive disorders in older adults
R Adams, ES Oh, S Yasar, CG Lyketsos, JS Mammen
JAMA internal medicine 183 (12), 1324-1331, 2023
112023
Partial identifiability in discrete data with measurement error
N Finkelstein, R Adams, S Saria, I Shpitser
Uncertainty in Artificial Intelligence, 1798-1808, 2021
92021
Learning Time Series Segmentation Models from Temporally Imprecise Labels
RJ Adams, BM Marlin
The Conference on Uncertainty in Artificial Intelligence (UAI), 2018
82018
Parsing wireless electrocardiogram signals with context free grammar conditional random fields
T Nguyen, RJ Adams, A Natarajan, BM Marlin
2016 IEEE Wireless Health (WH), 1-8, 2016
52016
Partial identifiability in discrete data with measurement error
N Finkelstein, R Adams, S Saria, I Shpitser
arXiv preprint arXiv:2012.12449, 2020
42020
The impact of time series length and discretization on longitudinal causal estimation methods
R Adams, S Saria, M Rosenblum
arXiv preprint arXiv:2011.15099, 2020
32020
1429: lead time and accuracy of TREWS, a machine learning-based sepsis alert
S Saria, K Henry, H Soleimani, R Adams, A Zhan, N Rawat, E Chen, A Wu
Critical Care Medicine 50 (1), 717, 2022
22022
Evaluating adoption, impact, and factors driving adoption for TREWS, a machine learning-based sepsis alerting system
KE Henry, R Adams, C Parent, A Sridharan, L Johnson, DN Hager, ...
medRxiv, 2021
22021
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Articles 1–20