INVESTIGATING THE ROLE OF ARTIFICIAL INTELLIGENCE IN DENTAL DIAGNOSTICS AND TREATMENT PLANNING – A COMPARATIVE STUDY
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Keywords
Artificial Intelligence in Dentistry, AI-assisted Dental Diagnostics, AI in Treatment Planning, Dental Technology and AI Integration
Abstract
Background:
Artificial Intelligence (AI) has emerged as a transformative technology in healthcare, providing advanced tools for diagnostics and treatment planning. In dentistry, AI is showing significant potential to improve accuracy, reduce errors, and streamline decision-making processes. Despite these advancements, there remains a need to explore its full capacity, challenges, and benefits in the realm of dental diagnostics and treatment planning.
Objective:
The primary objective of this study was to investigate the role of AI in enhancing dental diagnostic accuracy and optimizing treatment planning. The study aimed to evaluate how AI-driven tools perform in comparison to traditional methods and assess their potential impact on clinical outcomes.
Method:
This study analyzed 500 dental patients aged 18 to 65 with various oral health conditions who underwent diagnostics and treatment planning using AI-based systems from January 2020 to July 2023. AI tools such as convolutional neural networks (CNNs) integrated into CBCT, panoramic radiographs, and intraoral cameras were used, with software including VideaAI and Pearl Dental AI. Data collected from electronic health records (EHR) focused on diagnostic accuracy and treatment outcomes. Statistical analysis was conducted using SPSS version 27.0, comparing AI performance with traditional methods through paired t-tests using level of significance<0.05.
Results:
AI-driven diagnostics demonstrated high accuracy, with 94% sensitivity and 91% specificity in identifying dental conditions like caries and periodontal disease. The AI software showed a positive predictive value (PPV) of 90% and a negative predictive value (NPV) of 92%. AI treatment plans had an 87% success rate compared to 82% for traditional methods, and diagnostic time was reduced by 35%. The findings confirm that AI significantly enhances both diagnostic accuracy and efficiency in dental care.
Conclusion:
The study concludes that AI holds significant promise in dental diagnostics and treatment planning, improving both accuracy and efficiency. However, the adoption of AI in routine clinical practice requires addressing the existing challenges related to training, infrastructure, and acceptance among dental professionals. Continued research, integration of AI into dental education, and further technological advancements will be crucial in realizing its full potential in dentistry.
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Dr. Anjum Younus
BDS, MDS, MBA-MHM Assistant Professor, Department of Community & Preventive Dentistry
Liaquat College of Medicine & Dentistry Karachi
Dr Abdul Aleem
BDS, MCPS Senior Registrar, Department of Community Dentistry Karachi Medical and Dental College,Karachi Metropolitan University PhD Scholar, SIOHS Jinnah Sindh Medical University
Dr Zubia Waqar
B.D.S, MSc Public Health (UK), MSc Health Professions Education, PhD Scholar Dental Health Sciences, Jinnah Sindh Medical University (JSMU) Department of Medical Education, Indus University of Health Sciences - Indus Hospital & Health Network (IUHS-IHHN)
Dr Samra Bokhari
Senior Registrar, National Institute of Child Health Karachi BDS, FCPS, M-Orth, MBA (HHCM), CHPE, PhD Scholar SIOHS Jinnah Sindh Medical University
Dr Sana Adeeba Islam
MSc(UK),BDS,CHPE Associate Professor, Head Of Department, Community Dentistry, Karachi Medical and Dental College Karachi Metropolitan University
Dr Nabeel Khan
BDS, PGD, MS, CHPE, Assistant Professor, Oral Biology Department, Karachi Medical and Dental College,Karachi Metropolitan University