Automated Agents for Personalized Orthodontic Tooth Leveling
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Solution Overview
Problem
Current orthodontic treatment systems lack effective methods for providing personalized tooth leveling recommendations, failing to adequately account for patient-specific characteristics and doctor preferences, which hinders the design and visualization of appropriate orthodontic appliances.
Innovation Solution
The development of automated systems that utilize latent leveling factors to associate historical treatment data with specific patient types and doctors, enabling the derivation of tailored tooth leveling recommendations through machine learning algorithms, which are then stored in a database for use in orthodontic treatment planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated systems with machine learning algorithms are implemented to provide personalized tooth leveling recommendations, then the precision and personalization of treatment plans is improved, but the device complexity and implementation difficulty increases
Solution Approach 1:
The patent introduces automated agents as intermediary components that mediate between historical treatment data and treatment recommendations. These agents use machine learning algorithms to process complex data relationships and generate personalized tooth leveling recommendations, thereby improving precision while managing system complexity through modular architecture.
Solution Approach 2:
The system performs preliminary actions by gathering and processing historical treatment data before actual treatment planning. Automated agents analyze past treatment outcomes and patient characteristics in advance, creating a knowledge base that enables more precise recommendations without increasing the complexity of the actual treatment delivery process.
2Adaptability or versatility
If historical treatment data is gathered and processed to derive personalized recommendations, then the adaptability to patient-specific characteristics is improved, but the loss of time for data processing and analysis increases
Solution Approach 1:
The system performs preliminary data processing by gathering and analyzing historical treatment data in advance of actual treatment planning. Automated agents process patient characteristics, treatment outcomes, and clinical parameters beforehand, creating pre-computed recommendations that reduce real-time processing requirements and enable rapid deployment of personalized treatment plans.
Solution Approach 2:
The patent uses copying by creating digital representations of historical treatment data and patient characteristics. Automated agents analyze these digital copies to derive patterns and recommendations without requiring access to original patient records during treatment planning, thereby reducing time loss while maintaining high adaptability to patient-specific characteristics.
3Reliability
If automated agents use machine learning to associate historical data with patient types and doctors, then the reliability of treatment recommendations is improved, but the difficulty of detecting and measuring system performance increases
Solution Approach 1:
The patent implements feedback mechanisms where automated agents continuously learn from treatment outcomes and adjust their recommendations accordingly. The system measures performance by comparing predicted tooth leveling outcomes with actual treatment results, using this feedback to improve the reliability of recommendations over time while providing quantifiable metrics for system performance evaluation.
Solution Approach 2:
The system replaces manual assessment methods with automated machine learning algorithms that objectively measure and evaluate treatment outcomes. This substitution enables more reliable and consistent performance measurement compared to subjective clinical assessment, allowing for automated detection of system effectiveness through data-driven metrics.
Data Source
AI summary
Provided herein are methods and apparatuses for recommending tooth leveling (e.g., one or more of anterior leveling, posterior leveling, and arch-shape recommendations) for orthodontic devices and methods for patients. Factors involved in the leveling of teeth can include symmetry, doctor preferences, preferences regarding gender, the country in which the patient is being treated, and other issues related to the aesthetics of the mouth and arch shape. The device can comprise an aligner configured to fit over a patient's teeth. Methods of designing and manufacturing aligners based on leveling recommendations are also provided.