Knowledge, Attitudes and Perception towards Artificial Intelligence and Robotics in Dentistry- A Cross-Sectional Survey

Authors

  • Wajiha Zia
  • Mehwash Kashif
  • Abdul Aleem
  • Irum Munir Raja
  • Amna Rehman
  • Atif Iqbal Butt

Keywords:

Artificial intelligence, digitization systems, robotics, machine learning, dentistry, dentist

Abstract

OBJECTIVE: To evaluate dentists' knowledge, attitude and perception of robotics(R) and artificial intelligence (AI).

METHODOLOGY: Data were gathered for this cross-sectional survey from dental schools in Karachi that were both public and private. A total of 550 surveys were delivered through Google Forms. Dental students, graduates, postgraduates, and professionals of both sexes aged 20-70 years were included.  Participants were chosen by convenience sampling using non-probability. Data were analyzed using descriptive analysis and the Chi-square test in SPSS version 22.0.

RESULTS:  Of the 550 participants, men comprised 33% (n=181) overall, while women comprised 67%(n= 369). Despite having a great understanding of AI and R, the majority of participants, 55.1%(n=304), also have a strong point of view. However, only 42.5%(n=234) of respondents were aware of the difference between AI and R and 55.2%(n=304) have prior knowledge about AI and R. Nevertheless, 58% (n=319) of dentists thought it would be helpful for future dental procedures. Only 16%(n=88) of respondents believe artificial intelligence will eventually replace dentists. Some applicants, 55.2%(n=304), proposed employing AI/R for therapy, and 51%(n=281) agreed to get treatment.

CONCLUSION: By evaluating dentists' knowledge, attitudes, and perceptions of these technologies, it is possible to understand better the implementation of robotics and AI in clinical practice. More education and training programmes for dental professionals would be beneficial, and more studies would be able to determine the best ways to integrate robotics and AI to enhance patient results.

References

Alexander B, John S. Artificial intelligence in dentistry: Current concepts and a peep into the future. Int J Adv Res. 2018; 6(12): 1105-8. doi: 10.21474/IJAR01/8242.

Yüzba??o?lu E. Attitudes and perceptions of dental students towards artificial intelligence. J Dent Educ. 2021 Jan; 85(1): 60-8. doi: 10.1002/jdd.12385. Epub 2020 Aug 26.

Tandon D, Rajawat J. Present and future of artificial intelligence in dentistry. J Oral Biol Craniofac Res. 2020 Oct 1; 10(4): 391-6. doi: 10.1016/j.jobcr.2020.07.015. Epub 2020 Jul 24.

Liu J, Chen Y, Li S, Zhao Z, Wu Z. Machine learning in orthodontics: Challenges and perspectives. Adv Clin Exp Med. 2021; 30(10): 1065-74. doi: 10.17219/acem/138702.

Alhazmi A, Alhazmi Y, Makrami A, Masmali A, Salawi N, Masmali K et al. Application of artificial intelligence and machine learning for prediction of oral cancer risk. J Oral Pathol Med. 2021 May; 50(5): 444-50. doi: 10.1111/jop.13157. Epub 2021 Jan 17.

Revilla-León M, Gómez-Polo M, Vyas S, Barmak AB, Gallucci GO, Att W et al. Artificial intelligence models for tooth-supported fixed and removable prosthodontics: a systematic review. J Prosthet Dent. 2023; 129(2): 276-292. doi: 10.1016/j.prosdent.2021.06. 001. Epub 2021 Jul 17.

Hassani H, Amiri Andi P, Ghodsi A, Norouzi K, Komendantova N, Unger S. Shaping the Future of Smart Dentistry: From Artificial Intelligence (AI) to Intelligence Augmentation (IA). IoT. 2021; 2(3): 510-23. doi: 10.3390/iot2030026.

Abouzeid HL, Chaturvedi S, Abdelaziz KM, Alzahrani FA, AlQarni AA, Alqahtani NM. Role of Robotics and Artificial Intelligence in Oral Health and Preventive Dentistry -Knowledge, Perception and Attitude of Dentists. Oral Health Prev Dent. 2021; 19(1): 353-63. doi: 10.3290/j.ohpd.b1693873.

Grischke J, Johannsmeier L, Eich L, Griga L, Haddadin S. Dentronics: Towards robotics and artificial intelligence in dentistry. Dent Mater. 2020 Jun; 36(6): 765-78. doi: 10.1016/j.dental.2020.03.021. Epub 2020 Apr 27.

Roongruangsilp P, Khongkhunthian P. Artificial intelligence with the application in medicine and dentistry. J Osseointegration. 2022; 14(3): 166-173. doi: 10.23805/JO.2022. 14.22.

Kumar PR, Ravindranath KV, Srilatha V, Alobaoid MA, Kulkarni MM, Mathew T et al. Analysis of advances in research trends in robotic and digital dentistry: An original research. J Pharm Bioallied Sci. 2022 Jul; 14(Suppl 1): S185-S187. doi: 10.4103/jpbs.jpbs_59_22. Epub 2022 Jul 13.

Singh N, Pandey A, Tikku AP, Verma P, Singh BP. Attitude, perception and barriers of dental professionals towards artificial intelligence. J Oral Biol Craniofac Res. 2023; 13(5): 584-88. doi: 10.1016/j.jobcr.2023.06.006.

dos Santos DP, Giese D, Brodehl S, Chon SH, Staab W, Kleinert R et al. Medical students' attitude towards artificial intelligence: a multicentre survey. Eur Radiol. 2019 Apr; 29(4): 1640-1646. doi: 10.1007/s00330-018-5601-1. Epub 2018 Jul 6.

Kashif M, Mehmood K, Ayub T, Aslam M. Reasons and patterns of tooth extraction in a tertiary care hospital- A cross-sectional prospective survey. J Liaquat Uni Med Health Sci. 2014; 13(03): 125-29.

Abouzeid HL, Chaturvedi S, Abdelaziz KM, Alzahrani FA, AlQarni AA, Alqahtani NM. Role of Robotics and Artificial Intelligence in Oral Health and Preventive Dentistry-Knowledge, Perception and Attitude of Dentists. Oral Health Prev. Dent. 2021; 19(1): 353-63. doi: 10.3290/j.ohpd.b1693873.

Shan T, Tay FR, Gu L. Application of artificial intelligence in dentistry. J Dent Res. 2020; 100(3): 232-44. doi: 10.1177/ 0022034520969115.

Agrawal P, Nikhade P. Artificial intelligence in dentistry: past, present, and future. Cureus. 2022; 14(7): e27405. doi: 10.7759/cureus.27405.

Downloads

Published

05-04-2024

How to Cite

1.
Zia W, Kashif M, Abdul Aleem, Raja IM, Rehman A, Butt AI. Knowledge, Attitudes and Perception towards Artificial Intelligence and Robotics in Dentistry- A Cross-Sectional Survey. J Liaq Uni Med Health Sci [Internet]. 2024 Apr. 5 [cited 2024 Nov. 23];23(01):75-80. Available from: http://121.52.154.205/index.php/jlumhs/article/view/1261

Issue

Section

Short Survey / KAP Study / Short Report / Short communication