A NOVEL APPROACH TO PREDICT SUDDEN CARDIAC DEATH USING LOCAL FEATURE SELECTION AND MIXTURE OF EXPERTS

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EBRAHIMZADEH ELIAS; NAJJAR ARABI BABAK

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Journal: COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING) Year:2016 | Volume:7 | Issue:3 Page(s): 15-32

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Title

A NOVEL APPROACH TO PREDICT SUDDEN CARDIAC DEATH USING LOCAL FEATURE SELECTION AND MIXTURE OF EXPERTS

Author(s)

EBRAHIMZADEH ELIAS | NAJJAR ARABI BABAK | Issue Writer Certificate

Keywords

LOCAL FEATURE SELECTIONQ2

HEART RATE VARIABILITYQ3

MIIXTURE OF EXPERTSQ2

ELECTROCARDIOGRAM SIGNALQ2

SUDDEN CARDIAC DEATHQ2

Abstract

Sudden Cardiac Death (SCD) is caused by loss of heart function which ultimately stops heart from pumping blood throughout the body and therefore, claims the patient’s life within few minutes. Once detected, SUDDEN CARDIAC DEATHs could substantially decrease through applying medical procedures or instrumentations such as defibrillators. Nonetheless, effective approaches to SCD prediction, based on which doctors can make informed decisions, are yet to be discovered. This research aims to propose a novel approach to LOCAL FEATURE SELECTION with the assistance of the most accurate methodologies, which have formerly been developed in previous works of this team, for extracting features from nonlinear, time-frequency and classic processes. Furthermore, taking into consideration the existence of different features from different areas, the Mixture of Experts is put forward as a means of classification. The suggested methods enable us to select features that differ from one another in each minute before the incidence through the agency of optimal feature selection in each one-minute period of the signal. Not only will this facilitate increasing the prediction time from 4 minutes to 12 with a high level of accuracy, but it also will provide us with an opportunity to interpret clinical signs considering the plurality of features in each minute. Additionally, applying the Mixture of Experts classification proceeds to ensure a precise decision-making on the output of different areas processes. The results indicate to the superiority of the proposed method to those mentioned in similar studies.

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APA: Copy

EBRAHIMZADEH, ELIAS, & NAJJAR ARABI, BABAK. (2016). A NOVEL APPROACH TO PREDICT SUDDEN CARDIAC DEATH USING LOCAL FEATURE SELECTION AND MIXTURE OF EXPERTS. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), 7(3), 15-32. SID. https://sid.ir/paper/203034/en

Vancouver: Copy

EBRAHIMZADEH ELIAS, NAJJAR ARABI BABAK. A NOVEL APPROACH TO PREDICT SUDDEN CARDIAC DEATH USING LOCAL FEATURE SELECTION AND MIXTURE OF EXPERTS. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)[Internet]. 2016;7(3):15-32. Available from: https://sid.ir/paper/203034/en

IEEE: Copy

ELIAS EBRAHIMZADEH, and BABAK NAJJAR ARABI, “A NOVEL APPROACH TO PREDICT SUDDEN CARDIAC DEATH USING LOCAL FEATURE SELECTION AND MIXTURE OF EXPERTS,” COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), vol. 7, no. 3, pp. 15–32, 2016, [Online]. Available: https://sid.ir/paper/203034/en

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