Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/39302
Title: Patient-specific inference and situation-dependent classification using Context-Sensitive Networks.
Authors: Joshi, R. 
Leong, T.Y. 
Issue Date: 2006
Source: Joshi, R.,Leong, T.Y. (2006). Patient-specific inference and situation-dependent classification using Context-Sensitive Networks.. AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium : 404-408. ScholarBank@NUS Repository.
Abstract: Representations and inferences that capture a formal notion of "context" are needed to effectively support various analytic and learning tasks in many biomedical applications. In this paper, we formulate patient-specific inference and situation-dependent classification as context-aware reasoning tasks that can be effectively supported in probabilistic graphical networks. We introduce a new probabilistic graphical framework of Context Sensitive Networks (CSNs) to efficiently represent and reason with context-sensitive knowledge. We illustrate how different types of inference in these networks can be handled in a context-dependent manner. We also demonstrate some promising evaluation results based on a set of real-life risk prediction and model classification problems in coronary heart disease.
Source Title: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
URI: http://scholarbank.nus.edu.sg/handle/10635/39302
ISSN: 15594076
Appears in Collections:Staff Publications

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