Knowledge, Attitudes and Perceptions Regarding Artificial Intelligence and its Uses in Oral Radiology Among Dental Surgeons of Lahore

Shahzada Faiz Ahmad Khan; Muhammad Asif Shahzad; Ayma Syed; Ghulam Mohammad Paracha; Lubna Yousaf; Maleeha Naseer

doi:10.25301/JPDA.341.17

Author(s)

Shahzada Faiz Ahmad Khan Department of Oral and Maxillofacial Surgery, Azra Naheed Dental College, Lahore, Pakistan

Muhammad Asif Shahzad Department of Oral and Maxillofacial Surgery, Azra Naheed Dental College, Lahore, Pakistan

Ayma Syed Department of Community & Preventive Dentistry, Azra Naheed Dental College, Lahore, Pakistan

Ghulam Mohammad Paracha Department of Oral and Maxillofacial Surgery, Azra Naheed Dental College, Lahore, Pakistan

Lubna Yousaf Department of Community & Preventive Dentistry, Avicenna Dental College, Lahore, Pakistan

Maleeha Naseer Department of Oral and Maxillofacial Surgery, Azra Naheed Dental College, Lahore, Pakistan

Abstract

OBJECTIVE: To assess the knowledge, attitudes and perceptions of dentists in Lahore regarding the emergence of artificial intelligence (AI) and its future applications in the field of oral radiology. METHODOLOGY: A total of 300 dentists participated in our study. Data collection was done by sending Google forms to dental surgeons in Lahore. This descriptive study was carried out after approval from the ethical review committee of Azra Naheed Dental College, Lahore from July 2023 to February 2024. There were no age restrictions or gender discrimination in this study. RESULTS: Out of the 300 dentists who participated in the study, about 80% were already having the concept regarding AI and familiar with it, 70% agreed to the fact that they plan and expect to use AI for making clinical diagnoses, 53% agreed that the interpretation of complex radiographic cases would be the prime and key function of AI, and 56% were in agreement that AI in future would have a promising role in Pakistan. CONCLUSION: It was concluded in our study that dental professionals are familiar with AI concepts.

Publication Details

Page(s) 17-21

DOI 10.25301/JPDA.341.17

Published Journal: Journal of Pakistan Dental Association, Volume: 34, Issue: 1, Year: 2025

Request the full text from PASTIC

Keywords

Lahore, Artificial intelligence, dentists, Oral x-rays

References

Nagi R,Aravinda K,Rakesh N,Gupta R,Pal A,Mann AK. .2020 .Clinical applications and performance of intelligent systems in dental and maxillofacial radiology: a review. Imaging Sci Dent, 50 : 81-92.

.2019 .Radiological images and machine learning:Trends, perspectives, and prospects. Comput Biol Med, 02 : 354-70.

Hwang JJ,Jung YH,Cho BH,Heo MS .2019 .An overview of deep learning in the field of dentistry. Imaging Sci Dent, 49(1) : 1-7.

Ghods K,Azizi A,Jafari A,Ghods K. .2023 .Application of Artificial Intelligence in Clinical Dentistry, a Comprehensive Review of Literature. J Dent (Shiraz), 24 : 356-371.

Casalegno F,Newton T,Daher R,Abdelaziz M,Lodi-Rizzini A,Schürmann F .2019 .Caries detection with near-infrared transillumination using deep learning. J Dent Res, 98 : 1227-33.

Thanathornwong B,Suebnukarn S B .2020 .Automatic detection of periodontal compromised teeth in digital panoramic radiographs using faster regional convolutional neural networks. Imaging Sci Dent, 50 : 169-74.

Oh S,Kim JH,Choi SW,Lee HJ,Hong J,Kwon SH .2019 .Physician confidence in artificial intelligence: an online mobile survey. J Med Internet Res, 21 : .

Hosny A,Parmar C,Quackenbush J,Schwartz LH,Aerts HJ .2018 .Artificial intelligence in radiology. Nat Rev Cancer, 18 : 500-510.

Wong SH,Al-Hasani H,Alam Z,Alam A .2019 .Artificial intelligence in radiology: how will we be affected? Eur Radiol. , 29 : 141-143.

Pesapane F,Codari M,Sardanelli F .2018 .Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine. Eur Radiol Exp, 24 : 35.

Farhadian M,Salemi F,Saati S,Nafisi N. .2019 .Dental age estimation using the pulp-to-tooth ratio in canines by neural networks. Imaging Sci Dent, 49 : 19-26.

Sam A,Currie K,Oh H,Flores-Mir C,Lagravére-Vich M .2019 .Reliability of different three-dimensional cephalometric landmarks in cone-beam computed tomography: A systematic review. Angle Orthod, 89 : 1-302.

Krishna AB,Tanveer A,Bhagirath PV,Gannepalli A,Orhan K,Bayrakdar IS,Ezhov M,Kravtsov A,Özyürek T,Chan CH,Huang TT,Chen CY,Lee CC,Chan MY,Chung PC .2019 .Texture-map-based branch-collaborative network for oral cancer detection. IEEE Trans Biomed Circuits Syst, 13 : 766-80.

.2018 .Contrast-enhanced computed tomography image assessment of cervical lymph node metastasis in patients with oral cancer by using a deep learning system of artificial intelligence. Oral Surg Oral Med Oral Pathol Oral Radiol, 10 : 458-63.

Ilhan B,Lin K,Guneri P,Wilder-Smith P .2020 .Improving oral cancer outcomes with imaging and artificial intelligence. J Dent Res, 99 : 241-8.

Welikala RA,Remagnino P,Lim JH,Chan CS,Rajendran S,Kallarakkal TG .2020 .Automated detection and classification of oral lesions using deep learning for early detection of oral cancer. IEEE Access, 8 : 132677-93.

Ahmad P,Alam MK,Aldajani A,Alahmari A,Alanazi A,Stoddart M,Sghaireen MG .2021 .Dental Robotics: A Disruptive Technology. Sensors (Basel), 21 : 3308.

Park WJ,Park JB .2018 .History and application of artificial neural networks in dentistry. Eur J Dent, 325 : 18-601.

Mupparapu M,Wu CW,Chen YC .2018 .Artificial intelligence, machine learning, neural networks, and deep learning: futuristic concepts for new dental diagnosis. Quintessence Int, 49 : 687-688.