Attitude, perception and barriers of dental professionals towards artificial intelligence

Singh, Nishi; Pandey, Anushka; Tikku, Aseem Prakash; Verma, Parul; Singh, Balendra Pratap

doi:10.1016/j.jobcr.2023.06.006

Cited by 11 publications

(6 citation statements)

References 21 publications

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“…However, most of them did not use AI in their dental practice or for research purposes. This finding is in agreement with previous studies [ 6 , 18 , 19 ]. This might be due to lack of awareness, lack of training in colleges, cost, and concerns regarding the potential for errors in the AI system that may not be easily identifiable, resulting in erroneous therapeutic decisions [ 18 , 20 ].…”

Section: Discussionsupporting

confidence: 95%

“…82% respondents felt that AI should be a part of their postgraduate curriculum and should be implemented in clinical practice. This finding is supported by previous studies [ 17 , 18 , 19 ]. Periodontitis presents a significant challenge for healthcare professionals in accurately identifying and diagnosing this condition.…”

Section: Discussionsupporting

confidence: 93%

“…The present study revealed that most senior lectures were aware of and had knowledge about AI compared to readers and professors. The reason for this phenomenon could potentially be attributed to the escalated level of contact that young individuals have with digitization, which encompasses their inclination to investigate and gain knowledge about novel technological advancements, such as AI [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

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Knowledge, Attitude and Perception Regarding Artificial Intelligence in Periodontology: A Questionnaire Study

Chawla,

Gadge,

Ronad

et al. 2023

Cureus

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Introduction: The utilization of artificial intelligence (AI) and machine learning (ML) models has brought about a significant transformation in the manner in which periodontists gather information, evaluate associated risks, develop diverse treatment alternatives, anticipate and diagnose dental conditions that compromise periodontal health. The principal objective of this prospective study was to examine periodontists’ understanding and acceptance of the application of AI in the realm of periodontology. Materials and methods: This observational study was conducted on 275 participants based on questionnaire using Google Forms. These forms were pre-validated and subsequently circulated among periodontists in Maharashtra via various social media platforms. The study, in its entirety, comprised four open-ended questions on participants’ demographics and 14 closed-ended questions, all of which were presented to the participants in English. These questions aimed to elicit participants' awareness, knowledge, attitudes, and perspectives regarding emerging applications of AI in the field of periodontology. To analyze the collected data, researchers employed the widely utilized Statistical Package for Social Sciences (SPSS) version 22.0. Result: A 75% response rate was achieved and 68% of the respondents were female. 62% periodontists were aware of AI; however, only 24% were aware of its working principles. Most respondents agreed with the use of AI in periodontal diagnosis; however, they disagreed with the use of AI in predicting clinical attachment loss (69%). 80-82% respondents felt that AI should be a part of postgraduate training and should be implemented in clinical practice. However, most periodontists do not use AI for diagnostic or research purposes. 49% periodontists felt that AI does not have better diagnostic accuracy than periodontists, and therefore cannot replace them in the future. Conclusion: Most periodontists possessed a reasonable level of understanding regarding the utilization of AI in the domain of periodontology and expressed a desire to incorporate it into their diagnostic and treatment planning processes for periodontal conditions. Additional endeavors must be undertaken to enhance periodontists’ awareness concerning the effective implementation of AI within their professional practice, with the aim of facilitating personalized treatment planning for their respective patients. It is postulated that the integration of AI will augment the likelihood of achieving favorable outcomes within the realm of periodontology.

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Section: Discussionsupporting

confidence: 95%

Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Knowledge, Attitude and Perception Regarding Artificial Intelligence in Periodontology: A Questionnaire Study

Chawla,

Gadge,

Ronad

et al. 2023

Cureus

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“…Hands-on experiential learning with real-world case examples could prove highly effective. Other reason is that lack of knowledge is an important barrier to the use of AI [ 42 ]. Notably, students from developed countries demonstrated greater AI knowledge than peers in developing nations.…”

Section: Discussionmentioning

confidence: 99%

Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis

Amiri,

Peiravi,

rezazadeh shojaee

et al. 2024

BMC Med Educ

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Background Nowadays, Artificial intelligence (AI) is one of the most popular topics that can be integrated into healthcare activities. Currently, AI is used in specialized fields such as radiology, pathology, and ophthalmology. Despite the advantages of AI, the fear of human labor being replaced by this technology makes some students reluctant to choose specific fields. This meta-analysis aims to investigate the knowledge and attitude of medical, dental, and nursing students and experts in this field about AI and its application. Method This study was designed based on PRISMA guidelines. PubMed, Scopus, and Google Scholar databases were searched with relevant keywords. After study selection according to inclusion criteria, data of knowledge and attitude were extracted for meta-analysis. Result Twenty-two studies included 8491 participants were included in this meta-analysis. The pooled analysis revealed a proportion of 0.44 (95%CI = [0.34, 0.54], P < 0.01, I2 = 98.95%) for knowledge. Moreover, the proportion of attitude was 0.65 (95%CI = [0.55, 0.75], P < 0.01, I2 = 99.47%). The studies did not show any publication bias with a symmetrical funnel plot. Conclusion Average levels of knowledge indicate the necessity of including relevant educational programs in the student’s academic curriculum. The positive attitude of students promises the acceptance of AI technology. However, dealing with ethics education in AI and the aspects of human-AI cooperation are discussed. Future longitudinal studies could follow students to provide more data to guide how AI can be incorporated into education.

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“…Almost the same number (42.5) was reported by Hamd et al [ 26 ], while the number of study participants was lower (134). Singh et al [ 24 ] reported 51.3% awareness among the 937 study participants. Sridhar et al [ 27 ] reported a 94.13% level of awareness among 460 participants.…”

Section: Reviewmentioning

confidence: 99%

Awareness and Approaches Regarding Artificial Intelligence in Dentistry: A Scoping Review

Aldakhil,

Alkhurayji,

Albarrak

et al. 2024

Cureus

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Background: Dentistry is one of the unique specialties that deals with both humans and machines. This fact illustrates the strong potential for artificial intelligence (AI) implementation in dentistry, which makes awareness and attitude toward AI an important indicator for the future of this technology in the field. Hence, this scoping review aimed to report the status of awareness and attitude toward AI in dentistry. Methodology: To ensure the quality and transparency of the present review, the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) flow chart is reported. Four databases were searched for related topics (Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica database (EMBASE), Google Scholar, and Scopus); 1,430 studies were identified, and after screening and filtering, 21 cross-sectional studies were included. Results: Twenty-one cross-sectional studies were included and yielded 7,688 participants. With an average level of 50.31% among all the studies that reported awareness (18 studies). Four subgroups’ average levels of awareness toward AI in dentistry were reported: 67.16% among dentists, 42.58% among dental students, 45.56% for studies conducted on both dentists and dental students, and 69.53% for studies reporting awareness of AI in oral radiology. Regarding attitude, out of 13 studies, an average level of 44.13% felt threatened or thought AI would replace them. Conclusion: The average level of awareness is in accordance with the attitude toward AI in dentistry. The low levels of awareness are important indicators of the gap formed between the inevitable application of AI and the lack of utilization in the dental field. AI implementation in dental schools’ curricula is required since the lowest reported level among subgroups was among dental students.

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Attitude, perception and barriers of dental professionals towards artificial intelligence

Cited by 11 publications

References 21 publications

Knowledge, Attitude and Perception Regarding Artificial Intelligence in Periodontology: A Questionnaire Study

Knowledge, Attitude and Perception Regarding Artificial Intelligence in Periodontology: A Questionnaire Study

Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis

Awareness and Approaches Regarding Artificial Intelligence in Dentistry: A Scoping Review

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