CHARACTERIZING SUBPOPULATIONS BY EXPOSURE RESPONSE

Characterizing subpopulations by their response to a given exposure relative to an alternative. Data for a set of subjects is received, including two exposures, two outcomes, and a set of characteristics. For a number of subsets an outcome model that estimates the probability of an outcome, given an...

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Main Authors Rosen-Zvi Michal, Parush Shear-Yashuv Naama, Goldschmidt Ya'ara, Flato Michal, Aharonov Ranit Y, El-Hay Tal
Format Patent
LanguageEnglish
Published 01.06.2017
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Abstract Characterizing subpopulations by their response to a given exposure relative to an alternative. Data for a set of subjects is received, including two exposures, two outcomes, and a set of characteristics. For a number of subsets an outcome model that estimates the probability of an outcome, given an exposure and the characteristics, is trained; an individual odds ratio (iOR), based on the outcome model, is computed; a sparse model that classifies subjects into a high-iOR group or another group is trained; the characteristics used in the sparse model are recorded; and, based on the recorded characteristics, a primary set of characteristics is selected. Another outcome model, based on the set of subjects and the characteristics, is trained. An iOR based on the other outcome model is computed. A sparse model for classifying subjects into a high-iOR group or another group, using the primary set of characteristics, is trained.
AbstractList Characterizing subpopulations by their response to a given exposure relative to an alternative. Data for a set of subjects is received, including two exposures, two outcomes, and a set of characteristics. For a number of subsets an outcome model that estimates the probability of an outcome, given an exposure and the characteristics, is trained; an individual odds ratio (iOR), based on the outcome model, is computed; a sparse model that classifies subjects into a high-iOR group or another group is trained; the characteristics used in the sparse model are recorded; and, based on the recorded characteristics, a primary set of characteristics is selected. Another outcome model, based on the set of subjects and the characteristics, is trained. An iOR based on the other outcome model is computed. A sparse model for classifying subjects into a high-iOR group or another group, using the primary set of characteristics, is trained.
Author Parush Shear-Yashuv Naama
Goldschmidt Ya'ara
Aharonov Ranit Y
El-Hay Tal
Flato Michal
Rosen-Zvi Michal
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– fullname: El-Hay Tal
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Snippet Characterizing subpopulations by their response to a given exposure relative to an alternative. Data for a set of subjects is received, including two...
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COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
Title CHARACTERIZING SUBPOPULATIONS BY EXPOSURE RESPONSE
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