Comparative study on the results of orthodontic diagnostics by using algorithms generated by Artificial Intelligence and simple algorithms

Introduction. Artificial intelligence (AI) is computer-generated intelligence, as opposed to the natural intelligence of humans and some animals. Kaplan and Haenlein define AI as “the ability of a system to correctly interpret external data, to learn from such data and use what it has learned to achieve specific goals and tasks through a flexible adaptation”. The term “artificial intelligence” is used colloquially to describe machines that mimic the “cognitive” functions that people associate with other human minds. One of the areas where technological advances have brought significant changes is orthodontics, especially in terms of diagnosis and orthodontic prediction. The aim of this study is to conduct a comparative analysis between the results obtained by using the complete algorithms that define Artificial Intelligence and the simple algorithms of classical medical software, used in the detection of the position and shape of teeth in various orthodontic anomalies. Methods. A group of 45 patients with maxillary-dento anomalies Angle Class I (DDM with crowding and deviation of the superior inter-incisive line) was studied. Two types of algorithms were used in the study group: modern type I algorithms and simple algorithms used in classical software to detect the position of the frontal teeth. Through the symmetrical points of the face the facial axes were determined, and after the detection of the contour of each tooth the incisional curve was calculated. The median line was analyzed against the vertical axis of the face, and the incisional curve towards the horizontal axis. Results. The study shows that AI algorithms offer an increased level of tooth position detection, compared to traditional softwares. Complex algorithms, specific to Artificial Intelligence, showed superior detection, and more stability in the analysis. Conclusion. Technological evolution and the development of machine learning capabilities have opened new perspectives in guiding orthodontic treatments through artificial intelligence (AI).