Validation for the placement and generation of components for dental restoration appliances

A computer-implemented method for using one or more machine learning models to automatically validate one or more characteristics of a digital representation of a dental restoration appliance component, the method comprising:

• receiving, by one or more computer processors, a first digital 3D oral care representation of an appliance component;
• receiving, by the one or more computer processors, a first digital 3D oral care representation of one or more teeth of a patient;
• using, by the one or more computer processors, a machine learning model, of the one or more machine learning models, to assign one or more result labels to the first digital 3D oral care representation of the appliance component, wherein the one or more result labels specify whether the appliance component is incorrectly formed or incorrectly placed;
• analyzing, by the one or more computer processors, the one or more result labels;
• automatically generating, by the one or more computer processors, output that specifies whether the appliance component is incorrectly formed or incorrectly placed;
• receiving, by the one or more computer processors, validation feedback information associated with the output, wherein the validation feedback information indicates whether the output correctly reflects an actual suitability of the appliance component for use;
• and
• automatically retraining, by the one or more computer processors, the machine learning model based on the validation feedback information, wherein the retrained machine learning model is used to assign result labels to subsequent digital representations of dental restoration appliance components.