Attitudes, perceptions and knowledge regarding the future of artificial intelligence in oral radiology among a group of dental students in Turkey: A survey

Gaye Keser; Filiz Mediha Namdar Pekiner

doi:10.33808/clinexphealthsci.928246

Research Article

Year 2021, Volume: 11 Issue: 4, 637 - 641, 26.10.2021

Gaye Keser Filiz Mediha Namdar Pekiner

https://doi.org/10.33808/clinexphealthsci.928246

Cited By: 3

Abstract

References

1. Oh S, Kim JH, Choi SW, Lee HJ, Hong J, Kwon SH. Physician confidence in artificial intelligence: an online mobile survey. J Med Internet Res 2019; 21: e12422.
2. Dreyer KJ, Geis JR. When machines think: radiology’s next frontier. Radiology 2017; 285: 713- 8.
3. Sur J, Bose S, Khan F, Dewangan D, Sawriya E, Roul A. Knowledge, attitudes, and perceptions regarding the future of artificial intelligence in oral radiology in India: A survey. Imaging Sci Dent 2020; 50:193-198.
4. Alsharqi M, Woodward WJ, Mumith JA, Markham DC, Upton R, Leeson P. Artificial intelligence and echocardiography.Echo Res Pract 2018; 5: R115-25.
5. Hwang JJ, Jung YH, Cho BH, Heo MS. An overview of deep learning in the field of dentistry. Imaging Sci Dent 2019; 49:1-7.
6. Bas B, Ozgonenel O, Ozden B, Bekcioglu B, Bulut E, Kurt M. Use of artificial neural network in differentiation of subgroupsof temporomandibular internal derangements: a preliminary study. J Oral Maxillofac Surg 2012; 70: 51-9.
7. Shaban M, Khurram SA, Fraz MM, Alsubaie N, Masood I, Mushtaq S, et al. A novel digital score for abundance of tumour infiltrating lymphocytes predicts disease free survival in oral squamous cell carcinoma. Sci Rep 2019; 9: 13341.
8. Bychkov D, Linder N, Turkki R, Nordling S, Kovanen PE, Verrill C, et al. Deep learning based tissue analysis predicts outcome in colorectal cancer. Sci Rep 2018; 8: 3395.
9. Johnston SC. Anticipating and training the physician of the future: the importance of caring in an age of artificial intelligence. Acad Med 2018; 93: 1105-6.
10. Lee JH, Kim DH, Jeong SN, Choi SH. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm. J Dent 2018; 77:106-111.
11. Poedjiastoeti W, Suebnukarn S. Application of Convolutional Neural Network in the Diagnosis of Jaw Tumors. Healthc Inform Res 2018;24: 236–241. doi: 10.4258/ hir.2018.24.3.236.
12. Faber J, Faber C, Faber P. Artificial intelligence in orthodontics. APOS Trends Orthod 2019;9: 201-205.
13. Woo SY, Lee SJ, Yoo JY, Han JJ, Hwang J. et al. Autonomous bone reposition around anatomical landmark for robotassisted orthognathic surgery. J Craniomaxillofac Surg 2017; 45: 1980‐1988. doi: 10.1016/j.jcms.2017.09.001.
14. Yüzbaşıoğlu E. Attitudes and perceptions of dental students towards artificial intelligence. J Dent Educ 2020 Aug 26. doi: 10.1002/jdd.12385.
15. Ranjana V; Gayathri R; Vishnu PV; Kavitha S. "Awareness on application of artificial intelligence in medicine among dental students - A survey". Journal of Contemporary Issues in Business and Government 2021; 27:3130-3142.

Attitudes, perceptions and knowledge regarding the future of artificial intelligence in oral radiology among a group of dental students in Turkey: A survey

Year 2021, Volume: 11 Issue: 4, 637 - 641, 26.10.2021

Gaye Keser Filiz Mediha Namdar Pekiner

https://doi.org/10.33808/clinexphealthsci.928246

Cited By: 3

Abstract

Objective: This study investigated knowledge, attitudes, and perceptions regarding the future of artificial intelligence (AI) for radiological diagnosis among a group of Turkish dental students.
Methods: An online survey was conducted consisting of 11 questions using Google Forms and circulated among 4th and 5th grade students at Marmara University, Faculty of Dentistry. The survey consisted of questions regarding participants’ recognition of and attitudes toward AI, their opinions on directions of AI development, and their perceptions about the future of AI in oral radiology. IBM SPSS Statistics 25.0 (IBM SPSS, Turkey) program is used for statistical analysis.
Results: The study group consists of 75 4th and 65 5th grades and a total of 140 students. Of the 140 participating dental students, 60.0 % were already familiar with the concept of AI, 92.9% agreed stated that they would like to use a software/program that can be helpful in radiological diagnosis and 37.9 % reported that AI would have a future in Turkey. Among two grades, there was no statistically significant difference of answers to questions regarding the future and role of artificial intelligence in oral radiology (p>0.05).
Conclusion: According to the findings of the study, most dental students were aware of AI, AI systems could be used to improve diagnostic accuracy when reading radiographs, and AI has a promising role in radiological diagnosis.

Keywords

Artificial Intelligence, Students, Dental, Awareness

References

1. Oh S, Kim JH, Choi SW, Lee HJ, Hong J, Kwon SH. Physician confidence in artificial intelligence: an online mobile survey. J Med Internet Res 2019; 21: e12422.
2. Dreyer KJ, Geis JR. When machines think: radiology’s next frontier. Radiology 2017; 285: 713- 8.
3. Sur J, Bose S, Khan F, Dewangan D, Sawriya E, Roul A. Knowledge, attitudes, and perceptions regarding the future of artificial intelligence in oral radiology in India: A survey. Imaging Sci Dent 2020; 50:193-198.
4. Alsharqi M, Woodward WJ, Mumith JA, Markham DC, Upton R, Leeson P. Artificial intelligence and echocardiography.Echo Res Pract 2018; 5: R115-25.
5. Hwang JJ, Jung YH, Cho BH, Heo MS. An overview of deep learning in the field of dentistry. Imaging Sci Dent 2019; 49:1-7.
6. Bas B, Ozgonenel O, Ozden B, Bekcioglu B, Bulut E, Kurt M. Use of artificial neural network in differentiation of subgroupsof temporomandibular internal derangements: a preliminary study. J Oral Maxillofac Surg 2012; 70: 51-9.
7. Shaban M, Khurram SA, Fraz MM, Alsubaie N, Masood I, Mushtaq S, et al. A novel digital score for abundance of tumour infiltrating lymphocytes predicts disease free survival in oral squamous cell carcinoma. Sci Rep 2019; 9: 13341.
8. Bychkov D, Linder N, Turkki R, Nordling S, Kovanen PE, Verrill C, et al. Deep learning based tissue analysis predicts outcome in colorectal cancer. Sci Rep 2018; 8: 3395.
9. Johnston SC. Anticipating and training the physician of the future: the importance of caring in an age of artificial intelligence. Acad Med 2018; 93: 1105-6.
10. Lee JH, Kim DH, Jeong SN, Choi SH. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm. J Dent 2018; 77:106-111.
11. Poedjiastoeti W, Suebnukarn S. Application of Convolutional Neural Network in the Diagnosis of Jaw Tumors. Healthc Inform Res 2018;24: 236–241. doi: 10.4258/ hir.2018.24.3.236.
12. Faber J, Faber C, Faber P. Artificial intelligence in orthodontics. APOS Trends Orthod 2019;9: 201-205.
13. Woo SY, Lee SJ, Yoo JY, Han JJ, Hwang J. et al. Autonomous bone reposition around anatomical landmark for robotassisted orthognathic surgery. J Craniomaxillofac Surg 2017; 45: 1980‐1988. doi: 10.1016/j.jcms.2017.09.001.
14. Yüzbaşıoğlu E. Attitudes and perceptions of dental students towards artificial intelligence. J Dent Educ 2020 Aug 26. doi: 10.1002/jdd.12385.
15. Ranjana V; Gayathri R; Vishnu PV; Kavitha S. "Awareness on application of artificial intelligence in medicine among dental students - A survey". Journal of Contemporary Issues in Business and Government 2021; 27:3130-3142.

There are 15 citations in total.

Details

Primary Language	English
Subjects	Health Care Administration
Journal Section	Articles
Authors	Gaye Keser 0000-0001-7564-4757 Filiz Mediha Namdar Pekiner 0000-0001-7426-5587
Publication Date	October 26, 2021
Submission Date	April 26, 2021
Published in Issue	Year 2021 Volume: 11 Issue: 4

Cite

APA	Keser, G., & Namdar Pekiner, F. M. (2021). Attitudes, perceptions and knowledge regarding the future of artificial intelligence in oral radiology among a group of dental students in Turkey: A survey. Clinical and Experimental Health Sciences, 11(4), 637-641. https://doi.org/10.33808/clinexphealthsci.928246
AMA	Keser G, Namdar Pekiner FM. Attitudes, perceptions and knowledge regarding the future of artificial intelligence in oral radiology among a group of dental students in Turkey: A survey. Clinical and Experimental Health Sciences. October 2021;11(4):637-641. doi:10.33808/clinexphealthsci.928246
Chicago	Keser, Gaye, and Filiz Mediha Namdar Pekiner. “Attitudes, Perceptions and Knowledge Regarding the Future of Artificial Intelligence in Oral Radiology Among a Group of Dental Students in Turkey: A Survey”. Clinical and Experimental Health Sciences 11, no. 4 (October 2021): 637-41. https://doi.org/10.33808/clinexphealthsci.928246.
EndNote	Keser G, Namdar Pekiner FM (October 1, 2021) Attitudes, perceptions and knowledge regarding the future of artificial intelligence in oral radiology among a group of dental students in Turkey: A survey. Clinical and Experimental Health Sciences 11 4 637–641.
IEEE	G. Keser and F. M. Namdar Pekiner, “Attitudes, perceptions and knowledge regarding the future of artificial intelligence in oral radiology among a group of dental students in Turkey: A survey”, Clinical and Experimental Health Sciences, vol. 11, no. 4, pp. 637–641, 2021, doi: 10.33808/clinexphealthsci.928246.
ISNAD	Keser, Gaye - Namdar Pekiner, Filiz Mediha. “Attitudes, Perceptions and Knowledge Regarding the Future of Artificial Intelligence in Oral Radiology Among a Group of Dental Students in Turkey: A Survey”. Clinical and Experimental Health Sciences 11/4 (October 2021), 637-641. https://doi.org/10.33808/clinexphealthsci.928246.
JAMA	Keser G, Namdar Pekiner FM. Attitudes, perceptions and knowledge regarding the future of artificial intelligence in oral radiology among a group of dental students in Turkey: A survey. Clinical and Experimental Health Sciences. 2021;11:637–641.
MLA	Keser, Gaye and Filiz Mediha Namdar Pekiner. “Attitudes, Perceptions and Knowledge Regarding the Future of Artificial Intelligence in Oral Radiology Among a Group of Dental Students in Turkey: A Survey”. Clinical and Experimental Health Sciences, vol. 11, no. 4, 2021, pp. 637-41, doi:10.33808/clinexphealthsci.928246.
Vancouver	Keser G, Namdar Pekiner FM. Attitudes, perceptions and knowledge regarding the future of artificial intelligence in oral radiology among a group of dental students in Turkey: A survey. Clinical and Experimental Health Sciences. 2021;11(4):637-41.