COMPARATIVE STUDY ON THE GUIDANCE OF ORTHODONTIC TREATMENTS THROUGH ARTIFICIAL INTELLIGENCE-BASED SOFTWARE AND CLASSIC SOFTWARE

Abstract

When it comes to guiding orthodontic treatments, our study aims to evaluate the effectiveness and benefits of software powered by artificial intelligence (AI) compared to traditional software. The software underwent a thorough evaluation to assess its performance, adaptability, and verbal communication. According to the findings, the software showed a remarkable ability to process and analyze information, resulting in more accurate planning of orthodontic treatments. Its adaptability has been found to be noteworthy, enabling it to identify and address individual patient conditions and problems with greater precision. With the help of this software, orthodontic treatments can be modified and improved in real time, considering the progress and alterations of the case throughout the treatment. Verbal communication through “speech recognize” AI algorithms contributes significantly to their long-term use and user satisfaction. Creating a comfortable and pleasant environment, this software improves the user experience and strengthens their relationship with technology. Comparatively, the classic software presented a lower level of performance and adaptability, and it was impossible to communicate verbally with the software interface. It is based on fixed rule settings and cannot individualize the orthodontic treatment. On the other hand, it uses standardized planning that can lead to unsatisfactory results or further adjustments. According to the comparative study, the artificial intelligence-based software improved the performance and adaptability of orthodontic treatments. Additionally, it enabled direct verbal communication, eliminating the need for a keyboard and a mouse. They can provide more precise guidance by collecting data and machine learning capabilities. However, it is crucial to consider the cost and security aspects of implementing and using this software in the orthodontic practice.

Keywords

• artificial intelligence
• performance
• adaptability
• interface
• opencv haar cascades
• orthodontics