Knowledge, attitudes, and perceptions regarding the future of artificial intelligence in oral radiology in Jazan, Saudi Arabia
Keywords:
Artificial Intelligence, Radiology, Dental Radiology, Knowledge, Attitude, SurveyAbstract
Context: Applications of AI in dentistry are interesting, especially in radiology, and can be a boon for novice practitioners. AI can help in the tracing of cephalometric landmarks; in the detection of caries, alveolar bone loss, and periapical pathosis; the auto-segmentation of the inferior alveolar nerve; the analysis of facial growth, and other similar tasks. Methods and Materials: An online survey was prepared using Google Forms and the link was distributed among dentists in Jazan. The questionnaire was divided into 3 sections (knowledge, attitudes, and future). The first part consisted of 4 questions about fundamental knowledge of AI. The second part consisted of 4 questions regarding the dentist’s attitudes towards AI. The final section consisted of 7 questions about the possible future of AI in dental radiology among dentists in Jazan. Statistical analysis used: The data was statistically analysed using PASW Statistics for Windows, version 18 (SPSS Inc., Chicago, USA). The chi-squared test was used, with a level of significance p<0.05.
Downloads
References
Oh S, Kim JH, Choi SW, et al. Physician Confidence in Artificial Intelligence: An Online Mobile Survey. J Med Internet Res. 2019;21.
Dreyer KJ, Raymond Geis J. When Machines Think: Radiology’s Next Frontier. Radiology. 2017;285:713–718.
Hwang JJ, Jung YH, Cho BH, et al. An overview of deep learning in the field of dentistry. Imaging Sci Dent. 2019;49:1–7.
Bychkov D, Linder N, Turkki R, et al. Deep learning based tissue analysis predicts outcome in colorectal cancer. Sci Rep. 2018;8.
Bas B, Ozgonenel O, Ozden B, et al. Use of artificial neural network in differentiation of subgroups of temporomandibular internal derangements: a preliminary study. J Oral Maxillofac Surg. 2012;70:51–59.
Shaban M, Khurram SA, Fraz MM, et al. A Novel Digital Score for Abundance of Tumour Infiltrating Lymphocytes Predicts Disease Free Survival in Oral Squamous Cell Carcinoma. Sci Rep. 2019;9:1–13.
Johnston SC. Anticipating and Training the Physician of the Future: The Importance of Caring in an Age of Artificial Intelligence. Acad Med. 2018;93:1105–1106.
Sur J, Dewangan D, Sawriya E, et al. Knowledge , attitudes , and perceptions regarding the future of artificial intelligence in oral radiology in India : A survey. 2020;193–198.
Pakdemirli E. Artificial intelligence in radiology: friend or foe? Where are we now and where are we heading? Acta Radiol Open. 2019;8:205846011983022.
Hosny A, Parmar C, Quackenbush J, et al. Artificial intelligence in radiology. Nat Rev Cancer. 2018;18:500–510.
Pesapane F, Codari M, Sardanelli F. Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine. Eur Radiol Exp. 2018;2:1–10.
Mupparapu M, Wu CW, Chen YC. Artificial intelligence, machine learning, neural networks, and deep learning: Futuristic concepts for new dental diagnosis. Quintessence Int. 2018;49:687–688
Published
How to Cite
Issue
Section
Copyright (c) 2022 International journal of health sciences
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Articles published in the International Journal of Health Sciences (IJHS) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant IJHS right of first publication under CC BY-NC-ND 4.0. Users have the right to read, download, copy, distribute, print, search, or link to the full texts of articles in this journal, and to use them for any other lawful purpose.
Articles published in IJHS can be copied, communicated and shared in their published form for non-commercial purposes provided full attribution is given to the author and the journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
This copyright notice applies to articles published in IJHS volumes 4 onwards. Please read about the copyright notices for previous volumes under Journal History.