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Katharine Henry
Katharine Henry
Data Scientist at Janssen R&D | PhD Computer Science from Johns Hopkins University
Verified email at jhu.edu
Title
Cited by
Cited by
Year
A targeted real-time early warning score (TREWScore) for septic shock
KE Henry, DN Hager, PJ Pronovost, S Saria
Science translational medicine 7 (299), 299ra122-299ra122, 2015
4722015
Fixed-dimensional acoustic embeddings of variable-length segments in low-resource settings
K Levin, K Henry, A Jansen, K Livescu
2013 IEEE workshop on automatic speech recognition and understanding, 410-415, 2013
1152013
A targeted real-time early warning score (TREWScore) for septic shock. Sci Transl Med 7: 299ra122
KE Henry, DN Hager, PJ Pronovost, S Saria
222015
Too many definitions of sepsis: can machine learning leverage the electronic health record to increase accuracy and bring consensus?
S Saria, KE Henry
Critical care medicine 48 (2), 137-141, 2020
212020
Comparison of automated sepsis identification methods and electronic health record–based sepsis phenotyping: improving case identification accuracy by accounting for …
KE Henry, DN Hager, TM Osborn, AW Wu, S Saria
Critical care explorations 1 (10), 2019
142019
Can Septic Shock Be Identified Early? Evaluating Performance Of A Targeted Real-Time Early Warning Score (trewscore) For Septic Shock In A Community Hospital: Global And …
K Henry, S Wongvibulsin, A Zhan, S Saria, D Hager
Am J Respir Crit Care Med 195, A7016, 2017
142017
Domain adaptation in machine translation
M Carpuat, III Hal Daumé, A Fraser, C Quirk, F Braune, A Clifton, A Irvine, ...
2012 Johns Hopkins summer workshop final report, 61-72, 2012
132012
Sensespotting: Never let your parallel data tie you to an old domain
M Carpuat, H Daumé III, K Henry, A Irvine, J Jagarlamudi, R Rudinger
Proceedings of the 51st Annual Meeting of the Association for Computational …, 2013
122013
63: Rews: Real-time early warning score for septic shock
K Henry, C Paxton, KS Kim, J Pham, S Saria
Critical Care Medicine 42 (12), A1384, 2014
102014
Quantifying and visualizing medication adherence in patients following acute myocardial infarction
J Wang, S Wongvibulsin, K Henry, S Fujita
AMIA Annual Symposium Proceedings 2017, 2299, 2017
62017
Automatic measurement of positive and negative voice onset time
K Henry, M Sonderegger, J Keshet
Thirteenth Annual Conference of the International Speech Communication …, 2012
52012
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, 1-6, 2022
32022
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
32022
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
Human–machine teaming is key to AI adoption: clinicians’ experiences with a deployed machine learning system
KE Henry, R Kornfield, A Sridharan, RC Linton, C Groh, T Wang, A Wu, ...
NPJ digital medicine 5 (1), 1-6, 2022
12022
1405: ASSESSING CLINICAL USE AND PERFORMANCE OF A MACHINE LEARNING SEPSIS ALERT FOR SEX AND RACIAL BIAS
R Adams, K Henry, H Soleimani, N Rawat, M Saheed, E Chen, A Wu, ...
Critical Care Medicine 50 (1), 705, 2022
12022
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
12022
Early Identification Of Gastrointestinal Bleeding Requiring Critical Care Using Machine Learning
H Soleimani, K Henry, A Zhan, P Pronovost, N Rawat, D Hager, S Saria
Am J Respir Crit Care Med 195, A7145, 2017
12017
Translating Machine Learning into Clinical Practice: Lessons from Development to Deployment
KE Henry
Johns Hopkins University, 2020
2020
D15 CRITICAL CARE: DO WE HAVE A CRYSTAL BALL? PREDICTING CLINICAL DETERIORATION AND OUTCOME IN CRITICALLY ILL PATIENTS: Can Septic Shock Be Identified Early? Evaluating …
K Henry, S Wongvibulsin, A Zhan, S Saria, D Hager
American Journal of Respiratory and Critical Care Medicine 195, 2017
2017
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