Health Data Transition Estimation Across Age Groups
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Solution Overview
Problem
Existing technologies struggle to accurately estimate future health-related data without requiring long-term health data of the same individual, limiting effective planning for health and asset management.
Innovation Solution
A data estimation device that acquires health-related data from different age groups, classifies and estimates transition destinations using an optimal transportation algorithm, and outputs future health data based on probability distributions and disease prediction models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If long-term health data of the same individual is used for estimation, then estimation accuracy is improved, but data collection difficulty and time requirement increase
Solution Approach 1:
The patent uses health data from multiple individuals of the same age group as a copy or surrogate for estimating the target individual's future health data. Instead of requiring long-term longitudinal data from one person, the system copies patterns from cross-sectional data of others in the same age group, thereby reducing data collection time while maintaining estimation accuracy.
Solution Approach 2:
The patent introduces an intermediary approach by using age-group-based health data patterns as a mediator between current health status and future health predictions. The system uses health data from the same age group as an intermediary reference to bridge the gap between present and future states, eliminating the need for direct long-term tracking of the same individual.
2Adaptability or versatility
If health data from multiple age groups is used for estimation, then estimation versatility is improved, but data processing complexity increases
Solution Approach 1:
The patent segments health data by age groups, creating distinct datasets for different age ranges. This segmentation allows the system to process and analyze health patterns specific to each age group separately, making the complex multi-group data manageable through structured organization and enabling versatile estimation across different age populations without overwhelming processing complexity.
3Measurement precision
If transition destination estimation is performed, then future health prediction accuracy is improved, but computational requirements increase
Solution Approach 1:
The patent applies partial action by focusing computational resources on estimating transition destinations for specific age groups and health parameters rather than processing all possible data combinations. The system performs targeted estimation based on the specific age group and health data available, reducing overall computational requirements while maintaining prediction accuracy for the intended application scope.
Data Source
AI summary
The data estimation device includes an acquisition unit, an estimation unit, and an output unit. The acquisition unit acquires health-related data of each person of different age groups. The estimation unit estimates the transition destination of the health-related data of the target person in a case where the age of the target person in the first age group becomes the second age group. The output unit outputs health-related data in a case where the age of the target person has increased based on the estimation result of the transition destination. With such a configuration, the data estimation device can support decision making related to a future health condition.