Artificial Intelligence (AI) based Decision-Making Model for Orthodontic Diagnosis and Treatment Planning

A system for providing orthodontic treatment options for use in orthodontic diagnosis or treatment planning, the system comprising at least one processor configured to:

• perform a rules-based expert system analysis on a given feature variable to produce expert system treatment options, the given feature variable representing an orthodontic feature of a patient, the expert system treatment options being fewer in number than a number of standard orthodontic treatment options that apply to orthodontic diagnosis, orthodontic treatment options, or both;
• apply a computer-implemented multi-component model to a given set of feature variables to produce multi-component model-based treatment options that include primary and secondary model-based treatment options;
• and
• compare the expert system treatment options to the multi-component model-based treatment options to determine disagreement or agreement between each other, wherein:
• if disagreement, the at least one processor is further configured to enable an expert to review the expert system treatment options and the multi-component model-based treatment options, and adapting at least one of the given feature variable, rules-based expert system analysis, or multi-component model based on feedback from the expert;
• and
• if agreement, the at least one processor is further configured to output the primary and secondary model-based treatment options to a clinician.

A non-transitory computer-readable medium for providing orthodontic treatment options for use in orthodontic diagnosis or treatment planning, the non-transitory computer-readable medium having encoded thereon a sequence of instructions which, when loaded and executed by at least one processor, causes the at least one processor to:

• perform a rules-based expert system analysis on a given feature variable to produce expert system treatment options, the given feature variable representing an orthodontic feature of a patient, the expert system treatment options being fewer in number than a number of standard orthodontic treatment options that apply to orthodontic diagnosis, orthodontic treatment options, or both;
• apply a computer-implemented multi-component model to a given set of feature variables to produce multi-component model-based treatment options that include primary and secondary model-based treatment options;
• and
• compare the expert system treatment options to the multi-component model-based treatment options to determine disagreement or agreement between each other, wherein:
• if disagreement, the sequence of instructions further causes the at least one processor to enable an expert to review the expert system treatment options and the multi-component model-based treatment options, and adapt at least one of the given feature variable, rules-based expert system analysis, or multi-component model based on feedback from the expert;
• and
• if agreement, the sequence of instructions further causes the at least one processor to output the primary and secondary model-based treatment options to a clinician.