Application of Machine Learning and Deep Learning Technology in the Field of Dentistry among Top Five Gross Domestic Product (GDP) Countries - A Scientometric Analysis

Abstract

Background: The Scientometric analysis of the articles helps to provide more useful information about the
field of research.
Aim: This study aims to evaluate the articles based on the application of deep learning and machine learning
in the field of Dentistry among top five Gross domestic product (GDP) countries.
Materials and Method: The articles related to Deep learning (DL) and Machine learning (ML) in the field
of Dentistry among top five GDP countries were retrieved from electronic databases such as Google Scholar,
Scopus and PubMed using keywords and MeSH terms. The parameters such as author name, number of
authorships, number of citations, year, place of the study, journal, type of article, field of dentistry, outcome
and implementation of deep learning and machine learning in dentistry were evaluated. The collected data
were analyzed and tabulated using descriptive analysis.
Results: Totally thirty seven number of articles regarding deep learning and machine learning in the field
of dentistry among top five GDP Countries were obtained. The maximum number of studies was published
in United States of America and minimum studies in Japan. The articles were published between the years
2001 and 2020 in different fields of Dentistry.
Conclusion: The Scientometric analysis of articles related to the use of deep learning and machine learning
in the field of Dentistry helps the researchers and dentists to have an idea about the trends and improvement
for better analysis and treatment in the future for greater benefit of patients.