Abstract
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.
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The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group No. (RG-1439-53).
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Alarifi, A., AlZubi, A.A. Memetic Search Optimization Along with Genetic Scale Recurrent Neural Network for Predictive Rate of Implant Treatment. J Med Syst 42, 202 (2018). https://doi.org/10.1007/s10916-018-1051-1
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DOI: https://doi.org/10.1007/s10916-018-1051-1