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Updated: Feb 5, 2026

Modeling Charcot-Marie-Tooth Disease In Vitro by Transfecting Mouse Primary Motoneurons
Published on: January 7, 2019
Developing Charcot-Marie-Tooth Disease Recognition System Using Bacterial Foraging Optimization Algorithm Based
Abdulaziz Abdullah Al-Kheraif1, Mohamed Hashem2, Mohammed Sayed S Al Esawy3
1Dental Biomaterials Research Chair, Dental Health Department, College of Applied Medical Sciences, King Saud University, P.O Box 10219, Riyadh, 11433, Saudi Arabia. aalkhuraif@ksu.edu.sa.
Abstract:
In the developing technology Charcot-Marie-Tooth (CMT) disease is one of the teeth diseases which are occurred due to the genetic reason. The CMT disease affects the muscle tissue which reduces the progressive growth of the muscle. So, the CMT disease needs to be recognized carefully for eliminating the risk factors in the early stage. At the time of this process, the system handles the difficulties while performing feature extraction and classification part. So, the teeth images are processed by applying the normalization method which eliminates the salt and pepper noise from data. From that, modified group delay function along with Cepstral coefficient features are extracted with effective manner. After that Bacterial Foraging Optimization Algorithm based features are selected. Then the selected features are examined by applying the Bacterial Foraging Optimization Algorithm based spiking neural network which successfully recognizes the CMT disease. At that point the productivity of the framework is assessed with the assistance of exploratory outcomes.
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