Myopia Risk Assessment System Using Sensitivity Parameters
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Solution Overview
Problem
Current methods for predicting the onset and progression of myopia are inaccurate and unreliable, failing to account for significant variance in pre-myopic and myopic populations, necessitating a more precise and reliable approach to assess risk over time.
Innovation Solution
A method and system that determine a subject's risk of myopia onset or progression by evaluating sensitivity parameters related to dioptric optical features, lifestyle, genetic history, and biometric data, using a combination of predictive models and machine learning algorithms to assign risk categories and calculate a final score based on these parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional predictive models are used for myopia onset and progression, then the evaluation process is simplified, but the accuracy and reliability of prediction are poor
Solution Approach 1:
The patent segments the myopia prediction problem into multiple independent parameter assessments (sensitivity parameters, dioptric optical parameters, lifestyle parameters, genetic parameters, biometric parameters) that are evaluated separately and then integrated. This segmentation allows each parameter to be measured with appropriate precision while maintaining an organized, manageable assessment framework.
Solution Approach 2:
The patent introduces sensitivity parameters as a new measurement dimension that quantifies individual responsiveness to dioptric optical changes. By adding this parameter and establishing reference value ranges through database comparison, the system transforms subjective visual experience into objective measurable data, significantly improving prediction accuracy without excessive complexity.
2Reliability
If multiple parameters are evaluated to improve prediction accuracy, then the reliability of myopia risk assessment is improved, but the complexity of the evaluation system increases
Solution Approach 1:
The patent creates a universal assessment framework that integrates multiple parameter types (sensitivity, dioptric, lifestyle, genetic, biometric) into a single cohesive myopia risk evaluation system. This multi-functional system can assess different aspects of myopia risk through unified methodology, improving reliability while avoiding the need for separate evaluation systems for each parameter type.
Solution Approach 2:
The patent implements feedback mechanisms by comparing individual parameter values against reference value ranges established from population databases. This feedback loop allows the system to automatically interpret complex multi-parameter data and provide meaningful risk categorization, reducing the perceived complexity for users while maintaining high assessment reliability.
3Measurement precision
If sensitivity parameters and multiple other factors are integrated, then the predictive power of the model is improved, but the difficulty of determining risk categories increases
Solution Approach 1:
The patent transforms the complex multi-parameter assessment into simplified risk categories by comparing parameter values against pre-established reference ranges. This parameter transformation approach converts difficult-to-interpret continuous data into discrete risk levels, maintaining high predictive power while significantly reducing the difficulty of determining final risk categories.
Solution Approach 2:
The patent introduces reference value ranges as intermediary standards that mediate between raw parameter measurements and final risk conclusions. These reference ranges act as a translation layer that simplifies the interpretation of complex parameter data, making risk category determination more accessible while preserving the nuanced information from multiple parameters.
Data Source
AI summary
A method and system for determining a risk of an onset or progression of myopia over a timeframe. The method includes determining a value of at least one parameter associated with vision condition of a subject, the at least one parameter including a sensitivity parameter of the subject, the sensitivity parameter being relative to the sensitivity of the subject to a variation of at least one dioptric optical feature of at least one ophthalmic lens placed in front of at least one eye of the subject. The method also includes determining the subject's risk of the onset or progression of myopia over the timeframe, based on the determined value of the at least one parameter.