Multiobjective Optimization Design of Spinal Pedicle Screws Using Neural Networks and Genetic Algorithm : Mathematical Models and Mechanical Validation
المؤلفون المشاركون
Chao, Ching-Kong
Amaritsakul, Yongyut
Lin, Jinn
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-07-31
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Short-segment instrumentation for spine fractures is threatened by relatively high failure rates.
Failure of the spinal pedicle screws including breakage and loosening may jeopardize the fixation integrity and lead to treatment failure.
Two important design objectives, bending strength and pullout strength, may conflict with each other and warrant a multiobjective optimization study.
In the present study using the three-dimensional finite element (FE) analytical results based on an L25 orthogonal array, bending and pullout objective functions were developed by an artificial neural network (ANN) algorithm, and the trade-off solutions known as Pareto optima were explored by a genetic algorithm (GA).
The results showed that the knee solutions of the Pareto fronts with both high bending and pullout strength ranged from 92% to 94% of their maxima, respectively.
In mechanical validation, the results of mathematical analyses were closely related to those of experimental tests with a correlation coefficient of −0.91 for bending and 0.93 for pullout (P<0.01 for both).
The optimal design had significantly higher fatigue life (P<0.01) and comparable pullout strength as compared with commercial screws.
Multiobjective optimization study of spinal pedicle screws using the hybrid of ANN and GA could achieve an ideal with high bending and pullout performances simultaneously.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Amaritsakul, Yongyut& Chao, Ching-Kong& Lin, Jinn. 2013. Multiobjective Optimization Design of Spinal Pedicle Screws Using Neural Networks and Genetic Algorithm : Mathematical Models and Mechanical Validation. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-473512
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Amaritsakul, Yongyut…[et al.]. Multiobjective Optimization Design of Spinal Pedicle Screws Using Neural Networks and Genetic Algorithm : Mathematical Models and Mechanical Validation. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-473512
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Amaritsakul, Yongyut& Chao, Ching-Kong& Lin, Jinn. Multiobjective Optimization Design of Spinal Pedicle Screws Using Neural Networks and Genetic Algorithm : Mathematical Models and Mechanical Validation. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-473512
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-473512
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر