Pregledni rad

From tradition to technology: artificial intelligence advancements in dental age estimation

Arofi Kurniawan ; Department of Forensic Odontology, Faculty of Dental Medicine Universitas Airlangga, Surabaya, Indonesia
Samith Taqiasha
Ivan Rachman
Tiara Lathifah Riyadi
Michelle Liong
Widya Ayu Satya Pratiwi
Marvin Hidayat
Anand Marya

Sažetak

Conventional dental age (DA) estimation methods, relying on visual and clinical assessments, have significant limitations, especially in large-scale incidents like mass disasters. Recent advancements in artificial intelligence (AI) have revolutionized this field, offering enhanced accuracy, efficiency, and the ability to handle large datasets. AI techniques, including machine learning (ML) models like random forest (RF) and support vector machine (SVM) and deep learning models such as convolutional neural networks (CNNs), have demonstrated superior performance compared to conventional methods. This review explores the evolution of dental age estimation methods from traditional visual and radiographic techniques to modern AI-assisted approaches. It discusses the benefits and challenges of implementing AI in forensic odontology, including the need for high-quality training data, effective algorithm selection, and robust preprocessing techniques.

Ključne riječi

artificial intelligence; dental age estimation; forensic odontology; legal identity

Hrčak ID:

324756

URI

https://hrcak.srce.hr/324756

Datum izdavanja:

23.12.2024.

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