Detecting dental problem related brain disease using intelligent bacterial optimized associative deep neural network
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Detecting dental problem related brain disease using intelligent bacterial optimized associative deep neural network Nourelhoda M. Mahmoud1 • H. Fouad2,3 • Omar Alsadon4 • Ahmed M. Soliman3 Received: 4 February 2020 / Revised: 8 March 2020 / Accepted: 30 March 2020 Ó Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Nowadays, a lot of people have the oral health problems due to continuous changes in the lifestyle such as the person’s speech which can be affected by the malocclusion in teeth and the crooked teeth. The dental problems can cause cavity and bacterial infection. The dental and speech problems mostly can be related to the Alzheimer disease, and cognitive changes. Therefore, the dental information is collected from patients and analyzed by applying intelligent machine learning techniques. The gathered dental information is normalized by standardized min max approach. Further, different statistical parameters are derived which are huge in dimension. The optimal features are selected using grey wolf optimized approach. The method effectively selects the optimum dental features and the selected features are processed using bacterial optimized associative deep neural network. The network collects the Alzheimer disease features and compare them with the collected dental features to establish the brain related issues with dental features. The efficiency of the system is evaluated using experimental results and discussion. Thus, the introduced intelligent bacterial optimized associative deep neural network recognizes the relationship up to 98.98% of accuracy which is the maximum accuracy compared to other methods. Further, IBADNN-based Alzheimer detection system approach attains maximum predicting and selecting disease features (precision 98.65% and recall 99.03%) whereas other approaches such as OLVQ (precision 95.03% and recall 96.23%), HACANN (precision 96.36% and recall 96.91%) and GCNN (precision 97.47% and recall 97.512%) and attains low predicting and selecting accuracy. Keywords Oral health Dental problems Alzheimer disease Cognitive changes Standardized min max approach Grey wolf optimized approach Bacterial optimized associative deep neural network
1 Introduction Alzheimer’s disease is a type of dementia that causes problems with memory, thinking and behavior. Symptoms usually develop slowly and get worse over time, becoming & H. Fouad [email protected] 1
Biomedical Engineering Department, Faculty of Engineering, Minia University, Minia, Egypt
2
Applied Medical Science Dept. CC, King Saud University, P.O Box 10219, Riyadh 11433, Saudi Arabia
3
Biomedical Engineering Department, Faculty of Engineering, Helwan University, P.O. Box 11795, Helwan 11792, Egypt
4
Dental Health Department, College of Applied Medical Sciences, King Saud University, P.O Box 10219, Riyadh 11433, Saudi Arabia
severe enough to interfere with daily tasks. According to the report issued by the University of Central Lancashire— Medical Scho
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