Knowledge, attitude, and perception of dentists regarding the role of Artificial Intelligence and its applications in Oral Medicine and Radiology: a cross sectional study

作者
Sridhar Murali,Anjana Bagewadi,Lokesh Kumar S,Anabelle Fernandes,T Jayapriya,Arun Panwar,Vaishali K. Keluskar
出处
期刊:Journal of oral medicine and oral surgery [EDP Sciences]
卷期号:29 (2): 22-22 被引量:46
标识
DOI:10.1051/mbcb/2023018
摘要

Background and objective:There is a paradigm shift in the medical and dental fields due to the introduction of artificial intelligence (AI). Since AI has a potential impact on current and future practitioners, understanding the basic concept, working principle, and likely applications of AI as a diagnostic tool in Oral Medicine and Radiology is necessary for its widespread use. Therefore, this study aims to assess the knowledge, attitude, and perception of dental students and dentists regarding the possible applications of AI in the field of Oral Medicine and Radiology.Materials and methods:This was a cross-sectional questionnaire-based study comprising 15 questions circulated through Google Forms® to 460 dental students and professionals. The questionnaire collected demographic data of participants and assessed their knowledge, perception, and attitude about AI in Oral Medicine and Radiology answered using a 5-point Likert scale. Responses obtained were statistically analyzed using descriptive statistics and a chi-square test.Results:Out of 460 participants, majority had an idea about AI (94.13%) and its working principle (73.30%). Participants agreed that AI can be used in the diagnosis and formulating of treatment plans (88.47%), early detection of cancer (77.82%), forensic dentistry (74.13%), and as a prognostic (80.65%) and quality control tool (81.30%). A majority felt that AI should be incorporated into the dental curriculum (92.39%) and most of them were against suggesting AI in clinical incorporation (35.87%) with a fear that AI might replace the clinician in the future (76.52%).Conclusion:Based on the findings of the study, we strongly recommend that further research and insights into AI should be delivered through lectures, curricular courses, and scientific meetings to explore and increase awareness about this fascinating technology.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
科研通AI6.2的应助被张张晶晶采纳,获得10
1秒前
1秒前
孙凤敏发布了新的文献求助10
1秒前
ysy0209发布了新的文献求助10
2秒前
2秒前
2秒前
jianji发布了新的文献求助10
4秒前
小齐爱科研完成签到,获得积分10
4秒前
jiangnan发布了新的文献求助30
4秒前
4秒前
YJL发布了新的文献求助10
4秒前
淡淡的向雁完成签到,获得积分10
7秒前
zl12345完成签到,获得积分10
7秒前
7秒前
橘子姜姜发布了新的文献求助10
8秒前
FashionBoy的应助被缓慢的凝云采纳,获得10
8秒前
8秒前
清漪发布了新的文献求助10
8秒前
讲座梅郎完成签到,获得积分10
8秒前
Leexxxhaoo发布了新的文献求助10
8秒前
Jasper的应助被大意的语薇采纳,获得10
9秒前
阚雨函完成签到 ,获得积分10
9秒前
伟大的娃娃完成签到,获得积分10
9秒前
迅速的怜寒完成签到 ,获得积分10
10秒前
万能图书馆的应助被孙凤敏采纳,获得10
10秒前
优惠券完成签到,获得积分10
10秒前
A小柴发布了新的文献求助10
11秒前
12秒前
12秒前
Namy发布了新的文献求助10
13秒前
丘比特的应助被jianji采纳,获得10
13秒前
Jrssion发布了新的文献求助10
14秒前
16秒前
微笑发布了新的文献求助10
16秒前
一口一完成签到 ,获得积分10
16秒前
HS完成签到,获得积分10
17秒前
XX关注了科研通微信公众号
17秒前
123完成签到,获得积分10
17秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
RNA结合蛋白调控丝状真菌次级代谢的分子机制及功能研究 2000
拉伸高分子熔体中缠结行为的模拟和小角中子散射研究 1080
Encyclopedia of Modern Artificial Intelligence 1000
Особенности технологий и методов информационно-психологических войн СССР с Великобританией и США в период 1939-1953 гг 1000
Critical Psychology 600
Analyses de reconnaissances de dettes passées devant les échevins d'Ypres (1249-1291) 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8145007
求助须知:如何正确求助?哪些是违规求助? 9544159
关于积分的说明 21660593
捐赠科研通 7730658
什么是DOI,文献DOI怎么找? 3422578
关于科研通互助平台的介绍 2547643
邀请新用户注册赠送积分活动 2465185