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Related Concept Videos

Teeth01:15

Teeth

373
The formation of teeth, also known as odontogenesis, is a complex process that begins in utero, around the sixth week of embryonic development. There are three stages to this process: the bud stage, the cap stage, and the bell stage.
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin...
373

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

Hang-Nga Mai1,2, Thaw Thaw Win3, Hyeong-Seob Kim4

  • 1Institute for Translational Research in Dentistry, Kyungpook National University, Daegu, Republic of Korea.

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Summary

Dental professionals

Keywords:
artificial intelligencecomputer‐aided design softwaredeep learningexplainable artificial intelligenceexploratory factor analysissatisfaction

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Area of Science:

  • Dental informatics
  • Human-computer interaction
  • Artificial intelligence in dentistry

Background:

  • Dental professionals utilize computer-aided design (CAD) software extensively.
  • Understanding user satisfaction is crucial for software development and adoption.

Purpose of the Study:

  • To analyze dental professional satisfaction with CAD software performance.
  • To apply deep learning (DL) and explainable artificial intelligence (XAI) for behavioral analysis.

Main Methods:

  • Surveyed 436 dental professionals with varying CAD experience.
  • Employed exploratory factor analysis and a multilayer perceptron artificial neural network (MLP-ANN).
  • Utilized permutation feature importance analysis (PFIA) and Shapley values for XAI insights.

Main Results:

  • MLP-ANN model achieved 95% accuracy, outperforming logistic regression.
  • Design adjustability was the key factor for user satisfaction.
  • Positive impact from finish line/crown design features; negative impact from design steps/installation time.

Conclusions:

  • Identified key factors influencing dental CAD software selection and usage.
  • Demonstrated DL-XAI as a viable approach for behavioral analysis in dentistry.
  • Provides insights for informed dental CAD software development and selection.