Cephalometry Analysis Of Orthodontic Treatment Using Artificial Intelligence Deep Learning Compared To Conventional Methods In Caucasoid Race - Indrawati, Silvia Vera; Wardhana, Erdianto Setya; Suhartono, Budi; Yusuf, Moh (Jurnal Medali, 2025)
Background: Cephalometry was a radiographic analysis used in orthodontic treatment to study dentofacial growth, diagnosis, treatment planning, and evaluation of treatment outcomes. Cephalometry was divided into two, conventional method cephalometry and Artificial Intelligence (AI). AI is an artificial intelligence technology that was used for chatbots, diagnostic aids, and electronic medical records. The purpose of this review was to analyze the cephalometry of orthodontic treatment using AI deep learning compared to conventional methods in the Caucasoid race. Method: The data collection method used is the PICO method by browsing the PUBMED, Science Direct, and Google Scholar electronic databases. The keywords used are Cephalometric Orthodontics AND Artificial Intelligence OR Digital AND Conventional AND Comparison. Result: The results of this review found significant differences between conventional methods and AI methods. AI in terms of time was able to outperform conventional methods with a speed of up to 13x. AI also excels in terms of efficiency because it saves manpower. Aspects of reliability, angular and linear measurements, and the value of AI had capabilities that were equivalent to humans and even more so that they can be recommended for use in dental practice. AI suffers from a shortage in terms of cost because the preparation of AI into software requires a large amount of cost compared to conventional methods, which were more affordable. Conclusion: The conclusion of this literature review was that the AI method more superior in terms of time, reliability, value, angle measurement, and liner, as well as efficiency, but had drawbacks in terms of cost.