Health Positioning Map Using Multi-Parameter Risk Clustering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional health evaluation methods fail to provide a comprehensive assessment of an individual's overall health level, focusing instead on specific diseases like diabetes and arteriosclerosis, thus lacking the ability to evaluate the degree of overall health.
Innovation Solution
A health function creation method and apparatus that acquire and process data related to health parameters, including autonomic nerve, biological oxidation, inflammation, and cognitive function, to create a health level positioning map, utilizing dimensionality reduction and machine learning to evaluate overall health.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional health evaluation methods focus on specific disease paths (diabetes, arteriosclerosis, cancer, etc.), then disease-specific risk assessment is improved, but the ability to evaluate overall health level deteriorates
Solution Approach 1:
The patent segments health evaluation into multiple independent disease-specific indices (cancer risk index, cardiovascular risk index, metabolic syndrome risk index, etc.), each calculated from relevant test items. This allows precise assessment of individual disease risks while maintaining the ability to evaluate overall health through comprehensive indexing.
Solution Approach 2:
The patent creates a universal health evaluation system that can assess multiple disease risks and overall health levels through a standardized framework. The system processes various test items (blood tests, imaging, physical exams) through a common algorithm to generate both specific disease indices and comprehensive health assessments, achieving multi-functionality.
2Adaptability or versatility
If comprehensive health data from multiple test items is collected, then overall health evaluation capability is improved, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary processing layer that standardizes and integrates data from diverse test items (blood tests, imaging, physical exams). This intermediary system converts heterogeneous medical data into unified numerical values that can be processed by the indexing algorithm, reducing system complexity while maintaining comprehensive evaluation capability.
Solution Approach 2:
The patent transforms complex medical test results into standardized numerical parameters suitable for mathematical processing. Test items are converted into quantifiable values with standardized units and scales, enabling their integration into the health index calculation framework without requiring complex handling of diverse data formats.
3Measurement precision
If multiple test items are measured to assess overall health, then evaluation comprehensiveness is improved, but measurement cost increases
Solution Approach 1:
The patent implements a flexible testing strategy where the full panel of test items is not always required. The system can function with a core set of essential tests for basic health assessment, with optional additional tests for more comprehensive evaluation. This partial action approach reduces measurement costs while maintaining adequate evaluation capability for most applications.
Data Source
AI summary
The present invention provides a method for creating a health level positioning map, the method including: acquiring a first data set for a first parameter set, for each of a plurality of examinees; processing the first data set to obtain first data; mapping the processed first data for each of the plurality of examinees; clustering the mapped first data and thereby specifying a plurality of regions; and characterizing at least some of the plurality of regions.