Prediction Model by Using Bayesian and Cognition-driven Techniques: A Study in the Context of Obstructive Sleep Apnea

Sim, Doreen Ying Ying and Chee, Siong Teh and Probir Kumar, Banerjee (2013) Prediction Model by Using Bayesian and Cognition-driven Techniques: A Study in the Context of Obstructive Sleep Apnea. Procedia - Social and Behavioral Sciences, 97. pp. 528-537. ISSN 1877-0428

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Abstract

This research proposes a mechanism for cost-effective medical diagnostic support for relatively new physical ailments or diseases where there are incomplete data sets available and hence, common parameters are forced to be used for drawing a- priori inferences. We propose a simple but powerful prediction model that combines the advantages of the Bayesian Approaches and Cognition-Driven Techniques such as Expert Reasoning (ER) and Cognitive Reasoning (CR) using Markov Chain analyses. Then, we demonstrate the effectiveness of our approach in predicting Obstructive Sleep Apnea (OSA).

Item Type: Article
Uncontrolled Keywords: diagnostic support; a-priori inferences; Bayesian Approaches and Cognition-Driven Techniques; Expert Reasoning (ER); Cognitive Reasoning (CR); Markov Chain analyses; Obstructive Sleep Apnea (OSA), unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development
Depositing User: Karen Kornalius
Date Deposited: 19 Sep 2017 07:30
Last Modified: 30 Jun 2021 17:00
URI: http://ir.unimas.my/id/eprint/17677

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