Artificial intelligence applications in dentistry

IF 3.1 2区医学 Q1 DENTISTRY, ORAL SURGERY & MEDICINE

Journal of the American Dental Association Pub Date : 2024-09-01 DOI:10.1016/j.adaj.2024.05.013

Fernanda Pretto Zatt DDS, MS, Aurélio de Oliveira Rocha DDS, MS, Lucas Menezes dos Anjos DDS, MS, Ricardo Armini Caldas DDS, MS, PhD, Mariane Cardoso DDS, MS, PhD, Gustavo Davi Rabelo DDS, MS, PhD

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引用次数: 0

Abstract

Background

The aim of this study was to understand the trends regarding the use of artificial intelligence in dentistry through a bibliometric review.

Types of Studies Reviewed

The authors performed a literature search on Web of Science. They collected the following data: articles—number and density of citations, year, key words, language, document type, study design, and theme (main objective, diagnostic method, and specialties); journals—impact factor; authors—country, continent, and institution. The authors used Visualization of Similarities Viewer software (Leiden University) to analyze the data and Spearman test for correlation analysis.

Results

After selection, 1,478 articles were included. The number of citations ranged from 0 through 327. The articles were published from 1984 through 2024. Most articles were characterized as proof of concept (979). Definition and classification of structures and diseases was the most common theme (550 articles). There was an emphasis on radiology (333 articles) and radiographic-based diagnostic methods (715 articles). China was the country with the most articles (251), and Asia was the continent with the most articles (871). The Charité–University of Medicine Berlin was the institution with the most articles (42), and the author with the most articles was Schwendicke (53).

Practical Implications

Artificial intelligence is an important clinical tool to facilitate diagnosis and provide automation in various processes.

查看原文本刊更多论文

人工智能在牙科中的应用：以该领域的计算研究趋势为重点的文献计量学综述。

背景：本研究旨在通过文献计量学综述了解人工智能在牙科中的应用趋势：作者在科学网上进行了文献检索。他们收集了以下数据：文章--引用次数和密度、年份、关键词、语言、文档类型、研究设计和主题（主要目标、诊断方法和专科）；期刊--影响因子；作者--国家、洲和机构。作者使用 Visualization of Similarities Viewer 软件（莱顿大学）分析数据，并使用斯皮尔曼检验进行相关性分析：经过筛选，共收录了 1,478 篇文章。引用次数从 0 到 327 不等。文章发表于 1984 年至 2024 年。大多数文章被定性为概念证明（979 篇）。结构和疾病的定义与分类是最常见的主题（550 篇）。重点是放射学（333 篇）和基于放射学的诊断方法（715 篇）。中国是发表文章最多的国家（251 篇），亚洲是发表文章最多的大陆（871 篇）。发表文章最多的机构是柏林夏里特大学（Charité-University of Medicine Berlin）（42篇），发表文章最多的作者是施文迪克（Schwendicke，53篇）：实践意义：人工智能是一种重要的临床工具，可促进诊断并实现各种流程的自动化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of the American Dental Association 医学-牙科与口腔外科

CiteScore

5.30

自引率

10.30%

发文量

221

审稿时长

34 days

期刊介绍： There is not a single source or solution to help dentists in their quest for lifelong learning, improving dental practice, and dental well-being. JADA+, along with The Journal of the American Dental Association, is striving to do just that, bringing together practical content covering dentistry topics and procedures to help dentists—both general dentists and specialists—provide better patient care and improve oral health and well-being. This is a work in progress; as we add more content, covering more topics of interest, it will continue to expand, becoming an ever-more essential source of oral health knowledge.