Deep learning and explainable artificial intelligence for investigating dental professionals' satisfaction with CAD software performance.

PURPOSE: This study aimed to examine the satisfaction of dental professionals, including dental students, dentists, and dental technicians, with computer-aided design (CAD) software performance using deep learning (DL) and explainable artificial intelligence (XAI)-based behavioral analysis concepts. MATERIALS AND METHODS: This study involved 436 dental professionals with diverse CAD experiences to assess their satisfaction with various dental CAD software programs. Through exploratory factor analysis, latent factors affecting user satisfaction were extracted from the observed variables. A multilayer perceptron artificial neural network (MLP-ANN) model was developed along with permutation feature importance analysis (PFIA) and the Shapley additive explanation (Shapley) method to gain XAI-based insights into individual factors' significance and contributions. RESULTS: The MLP-ANN model outperformed a standard logistic linear regression model, demonstrating high accuracy (95%), precision (84%), and recall rates (84%) in capturing complex psychological problems related to human attitudes. PFIA revealed that design adjustability was the most important factor impacting dental CAD software users' satisfaction. XAI analysis highlighted the positive impacts of features supporting the finish line and crown design, while the number of design steps and installation time had negative impacts. Notably, finish-line design-related features and the number of design steps emerged as the most significant factors. CONCLUSIONS: This study sheds light on the factors influencing dental professionals' decisions in using and selecting CAD software. This approach can serve as a proof-of-concept for applying DL-XAI-based behavioral analysis in dentistry and medicine, facilitating informed software selection and development.

User experience of and satisfaction with computer-aided design software when designing dental prostheses: A multicenter survey study.

AIM: The current study aimed to compare the responses and satisfaction reported by users with varying levels of experience when using different types of computer-aided design (CAD) software programs to design crowns. MATERIALS AND METHODS: A questionnaire was used to evaluate user responses to five domains (software visibility, 3Dscanned data preparation, crown design and adjustment, finish line registration, and overall experience) of various CAD software programs. The study included 50 undergraduate dental students (inexperienced group) and 50 dentists or dental technicians from two hospitals (experienced group). The participants used four different CAD software programs (Meshmixer, Exocad, BlueSkyPlan, and Dentbird) to design crowns and recorded the features using the questionnaire. Statistical analyses included one-way and two-way analysis of variance (ANOVA) tests to compare scores and verify the interaction between user response and experience. RESULT: User evaluation scores in the domains of software visibility and 3D-scanned data preparation varied between software programs (P < 0.001), with Exocad being favored by the experienced group. When evaluating crown design and finish line registration, Dentbird and Exocad scored significantly higher than the other software in both groups as they offered automation of the process using deep learning (P < 0.001). Two-way ANOVA showed that prior experience of using CAD significantly affected the users' responses to all queries (P < 0.001). CONCLUSION: User response and satisfaction varied with the type of CAD software used to design dental prostheses, with prior experience of using CAD playing a significant role. Automation of design functions can enhance user satisfaction with the software.

Revised evaluation objectives of the Korean Dentist Clinical Skill Test: a survey study and focus group interviews

PURPOSE: This study aimed to propose a revision of the evaluation objectives of the Korean Dentist Clinical Skill Test by analyzing the opinions of those involved in the examination after a review of those objectives. METHODS: The clinical skill test objectives were reviewed based on the national-level dental practitioner competencies, dental school educational competencies, and the third dental practitioner job analysis. Current and former examinees were surveyed about their perceptions of the evaluation objectives. The validity of 22 evaluation objectives and overlapping perceptions based on area of specialty were surveyed on a 5-point Likert scale by professors who participated in the clinical skill test and dental school faculty members. Additionally, focus group interviews were conducted with experts on the examination. RESULTS: It was necessary to consider including competency assessments for "emergency rescue skills" and "planning and performing prosthetic treatment." There were no significant differences between current and former examinees in their perceptions of the clinical skill test's objectives. The professors who participated in the examination and dental school faculty members recognized that most of the objectives were valid. However, some responses stated that "oromaxillofacial cranial nerve examination," "temporomandibular disorder palpation test," and "space management for primary and mixed dentition" were unfeasible evaluation objectives and overlapped with dental specialty areas. CONCLUSION: When revising the Korean Dentist Clinical Skill Test's objectives, it is advisable to consider incorporating competency assessments related to "emergency rescue skills" and "planning and performing prosthetic treatment."