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Shirazi M, Farahbod F, Alsharbaty M H. Emerging Applications of Artificial Intelligence in Modern Dentistry: Advancements, Challenges, and Future Directions. Journal title 2025; 14 (2) :1-6
URL: http://3dj.gums.ac.ir/article-1-649-fa.html
Emerging Applications of Artificial Intelligence in Modern Dentistry: Advancements, Challenges, and Future Directions. عنوان نشریه. 1404; 14 (2) :1-6

URL: http://3dj.gums.ac.ir/article-1-649-fa.html


چکیده:   (194 مشاهده)
The integration of artificial intelligence (AI) into modern dentistry represents a groundbreaking advancement with far-reaching implications. This article explores the evolution, applications, challenges, and future directions of AI in dental practice.
Originating in the mid-20th century, AI has evolved significantly, with neural networks emerging as a pivotal subset mimicking the human brain's structure. Deep learning, a subset of neural networks, enables autonomous data processing, revolutionizing diagnostics and therapies across medical disciplines.
In dentistry, AI's proliferation is driven by technological advancements and digitization. Dental diagnostics benefit from computer-generated second opinions, enhancing accuracy and efficiency. Neural networks expedite diagnosis processes, particularly in dental radiology, prompting extensive research and development. Beyond radiology, neural networks find applications across various dental specialties. In restorative dentistry, they aid in caries detection and restoration selection. In endodontics, they contribute to periapical lesion detection and treatment success prediction. Orthodontics benefits from neural networks in diagnosis and treatment planning, while dental surgery utilizes them in treatment planning and complication prediction. Additionally, AI facilitates periodontal evaluation and prediction based on psychological features.
Despite its numerous benefits, the integration of AI into dentistry necessitates further research to ensure seamless adoption and mitigate potential errors. Combining AI with conventional methodologies is advocated to minimize output discrepancies. Inter-professional collaboration among clinicians, researchers, and engineers is crucial for AI's development and integration, ultimately revolutionizing dental practice while prioritizing patient welfare.
 
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نوع مطالعه: Review article | موضوع مقاله: عمومى
دریافت: 1404/4/31 | پذیرش: 1404/5/10 | انتشار: 1404/5/10

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