Bayesian methods for the occurrence of REM among apnea patients
MetadataShow full item record
CitationMohd Saata, N. Z., Ibrahim, K., Jemain, A. A. ve AlMashoor, S. H. (2009). Bayesian methods for the occurrence of REM among apnea patients. Maltepe Üniversitesi. s. 296.
Studies on apnea patients are often carried out based on data obtained from the sleep study. Sleep stages that occurred during sleep is light sleep, deep sleep and Rapid Eye Movement (REM). The proportion of REM during sleep is di®erence according to gender, age group and Body Mass Index(BMI). Most apnea events occurred during REM sleep stages. Data on apnea subjects is quite scarce since high cost is required for conducting the study. Bayesian method is particularly suitable for analyzing limited data as it allows for updating of information by combining the current information with the prior belief. In this paper we demonstrate the use of Bayesian methods to rank the occurrence of REM for 22 apnea patients, based on the posterior mean of the rate of occurrence of REM. From the comparison of results using three di®erent prior distributions for the underlying rate of occurrence of REM, that is improper, gamma and log-normal priors, the ranking of patients in terms of severity of apnea are the same, regardless of the choice for the prior distributions, but the model ¯tting is found to be slightly better when based on gamma prior. Based on the sample, it is found that the most frequent case of REM experiences two episodes of REM for every two minutes.
SourceInternational Conference of Mathematical Sciences
- Makale Koleksiyonu 
The following license files are associated with this item: