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A Patient-Independent Significance Test by Means of False-Positive Rates in Selected Correlation Analysis of Brain Multimodal Monitoring Data
المؤلفون المشاركون
Faltermeier, Rupert
Proescholdt, Martin A.
Brawanski, Alexander
Wolf, Stefan
Bele, S.
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-08-08
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Recently, we introduced a mathematical toolkit called selected correlation analysis (sca) that reliably detects negative and positive correlations between arterial blood pressure (ABP) and intracranial pressure (ICP) data, recorded during multimodal monitoring, in a time-resolved way.
As has been shown with the aid of a mathematical model of cerebral perfusion, such correlations reflect impaired autoregulation and reduced intracranial compliance in patients with critical neurological diseases.
Sca calculates a Fourier transform-based index called selected correlation (sc) that reflects the strength of correlation between the input data and simultaneously an index called mean Hilbert phase difference (mhpd) that reflects the phasing between the data.
To reliably detect pathophysiological conditions during multimodal monitoring, some thresholds for the abovementioned indexes sc and mhpd have to be established that assign predefined significance levels to that thresholds.
In this paper, we will present a method that determines the rate of false positives for fixed pairs of thresholds (lsc, lmhpd).
We calculate these error rates as a function of the predefined thresholds for each individual out of a patient cohort of 52 patients in a retrospective way.
Based on the deviation of the individual error rates, we subsequently determine a globally valid upper limit of the error rate by calculating the predictive interval.
From this predictive interval, we deduce a globally valid significance level for appropriate pairs of thresholds that allows the application of sca to every future patient in a prospective, bedside fashion.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Faltermeier, Rupert& Proescholdt, Martin A.& Wolf, Stefan& Bele, S.& Brawanski, Alexander. 2018. A Patient-Independent Significance Test by Means of False-Positive Rates in Selected Correlation Analysis of Brain Multimodal Monitoring Data. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1132108
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Faltermeier, Rupert…[et al.]. A Patient-Independent Significance Test by Means of False-Positive Rates in Selected Correlation Analysis of Brain Multimodal Monitoring Data. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1132108
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Faltermeier, Rupert& Proescholdt, Martin A.& Wolf, Stefan& Bele, S.& Brawanski, Alexander. A Patient-Independent Significance Test by Means of False-Positive Rates in Selected Correlation Analysis of Brain Multimodal Monitoring Data. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1132108
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1132108
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
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