J Med Syst
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Comparative Study
Detecting sleep apnea by heart rate variability analysis: assessing the validity of databases and algorithms.
Obstructive sleep apnea (OSA) is a serious disorder caused by intermittent airway obstruction which may have dangerous impact on daily living activities. Heart rate variability (HRV) analysis could be used for diagnosing OSA, since this disease affects HRV during sleep. In order to validate different algorithms developed for detecting OSA employing HRV analysis, several public or proprietary data collections have been employed for different research groups. ⋯ In this paper, different algorithms employing HRV analysis were applied over diverse public and proprietary databases for detecting OSA, and the outcomes were validated in terms of a statistical analysis. Results indicate that the use of a specific database may strongly affect the performance of the algorithms, due to differences in methodologies of processing. Our results suggest that researchers must strongly take into consideration the database used when quoting their results, since selected cases are highly database dependent and would bias conclusions.
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Arterial blood gas (ABG) has an important role in the clinical assessment of patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD). Because of ABG complications, an alternative method is beneficial. We have trained and tested five artificial neural networks (ANNs) with venous blood gas (VBG) values (pH, PCO(2), HCO(3), PO(2), and O(2) saturation) as inputs, to predict ABG values in patients with AECOPD. ⋯ Subsequently, data from the remainder 26 patients was used for testing the networks. The ability of ANNs to predict ABG values and to detect significant hypercarbia was assessed and the results were compared with a linear regression model. Our results indicate that the ANNs provide an accurate method for predicting ABG values from VBG values and detecting hypercarbia in AECOPD.
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Disasters are fortunately rare occurrences. However, accurate and timely information and communication are vital to adequately prepare individual health organizations for such events. The current article investigates the health related communication and information systems for emergency management in Iran. ⋯ Recommendations were made for improving the national emergency management information and communication system. The findings have implications for health organizations in developing and developed countries especially in the Middle East. Creating disaster related information databases, creating protocols and standards, setting an information strategy, training staff and hosting a center for information system in the Ministry of Health to centrally manage and share the data could improve the current information system.