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Detection, Treatment Planning, and Genetic Predisposition of Bruxism: A Systematic Mapping Process and Network Visualization Technique

[ Vol. 20 , Issue. 8 ]

Author(s):

Md Belal Bin Heyat, Faijan Akhtar, Masood Hasan Khan, Najeeb Ullah, Ijaz Gul, Haroon Khan* and Dakun Lai*   Pages 755 - 775 ( 21 )

Abstract:


Background: Lack of sleep generates many disorders and bruxism is one of them. It has affected almost 31% of the world population.

Aim: The purpose of this paper is to determine the volume of the research conducted on bruxism and to create a database. We aimed to highlight critical issues for further research commitments and communications. This paper designs a comprehensive and very perception-based picture of bruxism disorder.

Methods: The research-based work uses three methods, including a systematic mapping process, network visualization, and literature review. Softwares, such as VOSviewer, MATLAB, and MEGA- X, have been utilized to analyze the work. We have researched deep insights of information to retrieve the present understanding of bruxism disorder from dental to psychological concepts, from engineering detection to clinical treatment, and from temporomandibular disorder to biological genes.

Results: We found 10 keywords and 77 items of bruxism in PubMed, Scopus, Google Scholar, and Web of Science databases based on previous publications. These keywords and items are helpful for all types of researchers, which include engineering, science, and medical background personals. 11 genes and 75 research articles with approximately 115,077 subjects, for the analysis of detection, treatment, child and adolescent bruxism, have been reviewed in the research work.

Conclusion: It has been found that bruxism altogether has sleep, neurological, dental, and genetic disorder components and is a complex phenomenon. This study has also mentioned the future direction and gap in research conducted so far on bruxism and has also tried to provide goals for the upcoming research to be accomplished in a more significant and scientific manner.

Keywords:

Adolescent, bruxism, children, diagnosis, genes, machine learning.

Affiliation:

Biomedical Imaging and Electrophysiology Laboratory, School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610054, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610054, Department of Oral Pathology and Oral Medicine, ZA Dental College and Hospital, Aligarh Muslim University, Aligarh, UP, 202002, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an, 710049, School of Life Science, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610054, Department of Pharmacy, Abdul Wali Khan University, Mardan 23200, Biomedical Imaging and Electrophysiology Laboratory, School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610054



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