SP-17 Ensuring Integrity in Dental Education: Developing a Novel AI Model for Consistent and Traceable Image Analysis in Preclinical Endodontic Procedures

CE Hours: 0.75

Description: Academic dishonesty in dental students is concerning. Students may attempt cheating in the simulation laboratory endodontic practical projects/exams through various methods. These methods include sample substitution, pre-preparation of samples, image manipulation, and presenting others' work as their own. Previous attempts to prevent cheating, such as marking teeth with nail polish or Sharpies, have proven ineffective, as they lack consistency and traceability. Implementing other effective countermeasures could require significant time, money, and effort. This presentation will introduce a novel AI model to ensure that images taken at various stages of endodontic projects/exams, from the preoperative to the final obturation radiograph, are consistent and traceable to the same sample tooth. This model leverages advanced image analysis techniques to authenticate each step of the dental procedure, thereby enhancing the integrity of dental education.

Learning Objectives:  

• Identify different methods to maintain academic integrity in preclinical endodontics.
• Describe the benefits and challenges of incorporating AI in endodontic education.
• Outline strategies for effectively integrating AI into endodontic education, focusing on how it can improve the assessment of students’ skills and deter academic dishonesty.