ARTIFICIAL INTELLIGENCE IN DENTISTRY: CLINICAL APPLICATIONS, LIMITATIONS, AND FUTURE PERSPECTIVES
DOI:
https://doi.org/10.56238/revgeov17n4-048Keywords:
Artificial Intelligence, Dentistry, Machine Learning, Deep Learning, Diagnostic Imaging, Clinical Decision-Making, Digital Dentistry, Predictive AnalyticsAbstract
Objective: To critically evaluate the current clinical applications of artificial intelligence (AI) in dentistry, as well as its limitations and future perspectives across different dental specialties.
Methodology: A narrative review was conducted through a comprehensive search of electronic databases, including PubMed, Scopus, and Google Scholar. Relevant studies published in English were selected based on their focus on AI applications in dentistry, including diagnostics, treatment planning, and outcome prediction. Articles were screened for relevance, and key findings were qualitatively synthesized.
Results: AI has demonstrated significant potential in multiple areas of dentistry, particularly in radiographic interpretation, caries detection, periodontal assessment, orthodontic planning, and oral pathology screening. Machine learning and deep learning models have shown high diagnostic accuracy, often comparable to or exceeding that of clinicians. However, important limitations persist, including data heterogeneity, lack of standardized datasets, limited external validation, and ethical concerns related to data privacy and algorithm transparency. Additionally, integration into routine clinical workflows remains challenging.
Conclusion: AI represents a transformative tool in modern dentistry, with the potential to enhance diagnostic precision and clinical decision-making. Despite promising advancements, its widespread adoption requires further validation, regulatory frameworks, and clinician training. Future research should focus on improving model generalizability, addressing ethical concerns, and ensuring seamless clinical integration.
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