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Non linear model-based prediction of cardiac output for depression and normal cases / Islam Ismail Mohamed Ahmed ; Supervised Khaled M. Wahba , Ahmad Taher Azar

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Islam Ismail Mohamed Ahmed , 2016Description: 113 P. : facsimiles ; 30cmOther title:
  • نموذج غير خطي إعتمادا علي التنبؤ بالنتاج القلبي لحالات الاكتئاب والحالات الطبيعيه [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering Summary: Mental Depression is associated with an increased risk of cardiovascular mortality, therefore, provisioning a generic simple nonlinear mathematical model for Cardiac Output (CO) of Depression and Normal cases could be an effective tool to investigate the effect of neuroleptic medication especially depression. The proposed models using System identification single input such as Heart Rate (HR) or Stroke Volume (SV) and single output such as CO in consistency with the Autoregressive which considered as a main role in nonlinear discrete system identification. 74 Depressed and 74 Normal peer cases are chosen to lie under research. Four models have been provided. However the obtained four general models for Depression and Normal cases could be a good contribution in neuroleptic medications field specially depression but HR showed the minimum average root mean square error (RMSE)
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Item type Current library Home library Call number Copy number Status Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.M.Sc.2016.Is.N (Browse shelf(Opens below)) Not for loan 01010110070881000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.M.Sc.2016.Is.N (Browse shelf(Opens below)) 70881.CD Not for loan 01020110070881000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering

Mental Depression is associated with an increased risk of cardiovascular mortality, therefore, provisioning a generic simple nonlinear mathematical model for Cardiac Output (CO) of Depression and Normal cases could be an effective tool to investigate the effect of neuroleptic medication especially depression. The proposed models using System identification single input such as Heart Rate (HR) or Stroke Volume (SV) and single output such as CO in consistency with the Autoregressive which considered as a main role in nonlinear discrete system identification. 74 Depressed and 74 Normal peer cases are chosen to lie under research. Four models have been provided. However the obtained four general models for Depression and Normal cases could be a good contribution in neuroleptic medications field specially depression but HR showed the minimum average root mean square error (RMSE)

Issued also as CD

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