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|Title:||Patient-specific inference and situation-dependent classification using Context-Sensitive Networks.||Authors:||Joshi, R.
|Issue Date:||2006||Citation:||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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