Memetic Search Optimization Along with Genetic Scale Recurrent Neural Network for Predictive Rate of Implant Treatment

被引:17
作者
Alarifi, Abdulaziz [1 ]
AlZubi, Ahmad Ali [1 ]
机构
[1] King Saud Univ, Dept Comp Sci, Community Coll, Riyadh, Saudi Arabia
关键词
Implant treatment; Teeth crown; Memetic search optimization along with genetic scale recurrent neural network; Patient characteristics; Sensitivity; Specificity and accuracy metrics;
D O I
10.1007/s10916-018-1051-1
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Implant treatment is one of the most important surgical processes in teeth which reduces the difficulties in teeth by providing the interface between bone and jaw. The established implant treatment used to support the denture, bridge and teeth crown. Even though it supports many dental related activities, the successive measure of implant treatment is fail to manage because it fully depends on the patient's personal activities and health condition of mouth tissues. So, the successive rate of implant treatment process is identified by applying the memetic search optimization along with Genetic scale recurrent neural network method. The introduced method analyzes the patient characteristics which helps to recognize the successive and failure rate of implant treatment process. The quality of the implant treatment of using simulation results in terms of sensitivity, specificity and accuracy metrics.
引用
收藏
页数:7
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