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Journals / Cumhuriyet Üniversitesi Fen-Edebiyat Fakültesi Fen Bilimleri Dergisi / 2017 / Cilt: 38 - Sayı: 2

Artificial Neural Networks Can be Used as Alternative Method to Estimate Loss Tooth Root Sizes for Prediction of Dental Implants

Dental İmplantlara Alternatif Değerlendirme Metodu Olarak Kayıp Dişlerin Boyutlarının Yapay Sinir Ağı Yöntemiyle Tahmini

Serkan AKKOYUN
Oğuzhan GÖRLER
Pages
385–395
Publication Date
2022-10-11
DOI
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AI Summary & Key Takeaways

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

According to the results, the method is convenient with this purpose.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of this study was to investigate the feasibility of estimation of canine root length and cervical width by an artificial neural network method with an appropriate setting.
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Key Findings & Data:We randomly obtained 120 representative samples of routine panoramic radiographs by computer tomography (CT).
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Conclusion & Impact:According to the results, the method is convenient with this purpose.
🔬Design:Modeling & Simulation
📍Scope:120 samples
⚙️Variables:Domain Parameters

Abstract

The aim of this study was to investigate the feasibility of estimation of canine root length and cervical width by an artificial neural network method with an appropriate setting. We randomly obtained 120 representative samples of routine panoramic radiographs by computer tomography (CT). Of 120 samples, 96 (80%) were used in training phase and 24 (20%) were used in test phase after a randomized selection. The intertuberal length (IL) of maxilla and canine root length (RL) and canine root cervical width (CW) of the right canine tooth was measured and was entered to a datum file. According to the results, the method is convenient with this purpose. The mean square error values are lied between 2% and 4.4% for the estimations. This shows that the ANN method is an alternative method for the canine root length and cervical width. The ANN software and system, which is a cost-effective tool to purchase, can be adapted to dental implant surgery after further study and optimization of software settings, allowing for the prediction of the size and width of implants in implant surgery.

Özet

Bu çalışmanın amacı, kanin diş kökü uzunluğu ve servikal genişliğinin yapay bir sinir ağı yöntemi (ANN) ile tahmin edilmesinin fizibilitesini araştırmaktır. Bilgisayarlı tomografilerin (BT) panoramic görüntüleri ile rasgele 120 hasta değerlendirildi. 120 örnekten 96'sı (% 80) eğitim fazında, 24'ü (% 20) randomize bir seçimden sonra test aşamasında kullanıldı. Sağ maksiller kanin kök uzunluğu (RL), servikal genişliği (CW) ve intertuberal uzunluk (IL) ölçülerek bir veri dosyasına oluşturuldu. Sonuçlara göre, yöntem bu amaca uygun bulundu. Tahminler için ortalama karesel hata değerleri %2 ile %4.4 arasında bulundu. Bu ANN yönteminin kanin kök boyu ve servikal genişliği için alternatif bir yöntem olduğunu göstermektedir. Satın alınabilecek uygun maliyetli bir araç olan ANN yazılımı ve sistemi, daha ileri çalışmalar ve yazılım ayarlarının optimizasyonundan sonra dental implant ameliyatına adapte edilebilir, implant ameliyatlarında implantların boy ve genişlikleri için öngörü imkanı verebilir.

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Cite This Article

AKKOYUN, S., GÖRLER, O. (2022). Artificial Neural Networks Can be Used as Alternative Method to Estimate Loss Tooth Root Sizes for Prediction of Dental Implants. Cumhuriyet Üniversitesi Fen-Edebiyat Fakültesi Fen Bilimleri Dergisi, Cilt: 38 - Sayı: 2, 385–395. https://ajindex.com/articles/480346

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