Perceptions of Dental Professionals Regarding the Role of Artificial Intelligence in Radiographic Assessment and Treatment Planning
DOI:
https://doi.org/10.61919/cwdbny69Keywords:
Artificial intelligence, Attitude, Dentistry, Perception, Radiographic assessment, Training, Treatment planningAbstract
Background: Artificial intelligence (AI) has rapidly advanced in medicine and dentistry, offering potential to enhance diagnostic accuracy, treatment planning, and data management. Despite global progress, integration of AI into dental practice in low- and middle-income settings remains limited. Awareness and confidence among dental professionals are critical determinants for successful adoption. Objective: To evaluate the knowledge, attitudes, and perceptions of dental professionals in Karachi regarding AI applications in radiographic assessment and treatment planning. Methods: A cross-sectional survey was conducted in February 2024 at three dental institutions in Karachi, Pakistan. A validated, structured questionnaire was distributed to undergraduate students, house officers, postgraduate residents, faculty, and private practitioners. Responses from 314 participants were analyzed using descriptive statistics and Chi-square tests in SPSS version 26.0, with statistical significance defined at p < 0.05. Results: Almost all participants (99.0%) reported familiarity with AI, though only 38.8% were extremely aware and 26.0% expressed high confidence in radiographic outputs. Strong endorsement was observed for AI in prognosis (76.0%), data storage (78.0%), forensic applications (72.0%), and education (81.0%). However, 70.0% agreed that radiologists could be replaced by AI, reflecting divided views on workforce implications. Conclusion: Dental professionals in Karachi perceive AI as highly valuable in education and practice but demonstrate limited confidence in its diagnostic reliability. Structured curricular integration and targeted training are essential to bridge the awareness–confidence gap and promote responsible adoption.
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The data supporting the findings of this study are available within the article.[its supplementary materials].
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Copyright (c) 2025 Kinza Mubbusher, Muhammad Ibrahim Usman Rabb, Abdul Raheem Qureshi, Shahid Islam (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
