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Journals / Türk Diş Hekimliği Araştırma Dergisi / 2026 / Cilt: 5 Sayı: 1

Artificial Intelligence in Periodontology: Current Applications, Innovations, and Future Perspectives

Periodontolojide Yapay Zeka Kullanımı: Günümüzdeki Uygulamalar, Yenilikler ve Gelecek

Erkin Erdoğan(Ege Üniversitesi Diş Hekimliği Fakültesi)0009-0002-8019-8098
Büşra Yılmaz(Ege Üniversitesi Diş Hekimliği Fakültesi)0000-0003-3631-3933
Gülnur Emingil(İstinye Üniversitesi Diş Hekimliği Fakültesi)0000-0002-4869-9629
Ali Gürkan0000-0001-5405-5689
Pages
61–78
Publication Date
2026-01-23
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Multicenter studies with large and diverse datasets are needed to develop robust, generalizable models and ensure the safe, reliable use of AI in periodontal care.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In recent years, artificial intelligence (AI) has transformed numerous aspects of healthcare, particularly in the analysis of medical imaging and decision support systems.
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Key Findings & Data:The findings highlight the effectiveness of deep learning in monitoring treatment outcomes, estimating risk, and enabling remote follow-up, while also contributing to personalized care strategies.
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Conclusion & Impact:Multicenter studies with large and diverse datasets are needed to develop robust, generalizable models and ensure the safe, reliable use of AI in periodontal care.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Yapay zeka · Periodontoloji · Derin öğrenme

Abstract

In recent years, artificial intelligence (AI) has transformed numerous aspects of healthcare, particularly in the analysis of medical imaging and decision support systems. In the field of dentistry, the application of AI is gaining momentum, especially for its ability to enhance diagnostic accuracy and clinical efficiency. Periodontology has emerged as a promising area where AI can contribute to disease detection, classification, prognosis, and patient monitoring. This review examines the current literature on AI applications in periodontology, focusing on models that utilize clinical, radiographic, and biological data. The findings highlight the effectiveness of deep learning in monitoring treatment outcomes, estimating risk, and enabling remote follow-up, while also contributing to personalized care strategies. Despite these promising developments, limitations such as restricted dataset diversity, single-center study designs, and unresolved ethical or legal concerns challenge the broader clinical integration of AI. Multicenter studies with large and diverse datasets are needed to develop robust, generalizable models and ensure the safe, reliable use of AI in periodontal care.

Özet

Son yıllarda yapay zeka teknolojileri, sağlık hizmetlerinde tanıdan tedaviye pek çok alanda dönüşüm yaratmıştır. Diş hekimliği özelinde, özellikle görüntüleme verilerinin analizi ve klinik karar destek sistemlerinin gelişimiyle birlikte, yapay zekanın potansiyeli giderek daha fazla önem kazanmaktadır. Periodontal hastalıkların teşhis, sınıflandırma, tedavi planlaması ve hasta takibi gibi alanlarında bu teknolojinin katkılarını ele alan güncel çalışmalar dikkat çekici bulgular sunmaktadır. Bu çalışmada, periodontoloji alanında yürütülen yapay zeka temelli araştırmalar değerlendirilmiş; klinik, radyografik ve biyolojik verilerin analizinde kullanılan yapay zeka modellerinin doğruluk, özgüllük ve duyarlılık düzeyleri karşılaştırılmıştır. Derin öğrenme algoritmalarının tedavi takibi, risk tahmini ve uzaktan hasta izleminde etkili olduğu ve kişiselleştirilmiş ağız sağlığı uygulamalarında da yenilikçi bir yaklaşım sunduğu gözlemlenmiştir. Bununla birlikte, sınırlı veri çeşitliliği, tek merkezli tasarımlar ve etik-yasal belirsizlikler, mevcut modellerin genellenebilirliğini ve klinik uygulanabilirliğini kısıtlamaktadır. Gelecekte, daha büyük ve temsili veri setleriyle yapılacak çok merkezli çalışmaların, yapay zekanın periodontoloji pratiğine güvenli ve etkili entegrasyonuna olanak sağlayacağı öngörülmektedir.

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Cite This Article

Erdoğan, E., Yılmaz, B., Emingil, G., Gürkan, A. (2026). Artificial Intelligence in Periodontology: Current Applications, Innovations, and Future Perspectives. Türk Diş Hekimliği Araştırma Dergisi, Cilt: 5 Sayı: 1, 61–78. https://doi.org/10.58711/turkishjdentres.vi.1691244

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