Gut Microbiome Risk Modeling for Personalized Disease Evaluation
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Solution Overview
Problem
Existing techniques do not provide a practical way to evaluate the risk of a subject developing a specific disease based on their intestinal flora information.
Innovation Solution
A model creation method using a computer to calculate a disease evaluation index by inputting diseases, extracting attribute and intestinal flora data from databases, and creating an association model to estimate disease risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If molecular biology techniques are used to analyze intestinal flora, then the complexity of culturing and observing bacteria is reduced, but the ability to provide practical disease risk evaluation for individuals is not achieved
Solution Approach 1:
The patent segments the complex intestinal flora analysis into manageable components: extracting specific bacterial group information from stool samples, associating this data with individual attributes (age, BMI, lifestyle), and processing it through statistical models to generate disease risk evaluations. This segmentation allows the complex biological analysis to be translated into practical individualized health assessments.
Solution Approach 2:
The patent introduces statistical models and algorithms as intermediaries between the raw intestinal flora data and the final disease risk evaluation. These intermediaries process the complex biological information through structured analysis (multiple logistic regression, structural equation modeling) to produce actionable health assessments for individuals.
2Adaptability or versatility
If statistical models are used to evaluate disease risk, then the practicality of individual evaluation is improved, but the complexity of data processing and model creation increases
Solution Approach 1:
The patent performs preliminary actions by pre-processing and structuring the data before model creation. Intestinal flora data from stool samples is extracted and organized, individual attributes are collected and standardized, and preliminary statistical analyses are conducted to identify significant relationships. This preparation simplifies the subsequent model creation and processing steps.
Solution Approach 2:
The patent transforms complex biological data into standardized statistical parameters and models. Intestinal flora composition is converted into quantifiable variables, lifestyle factors are standardized into comparable data points, and these parameters are processed through statistical algorithms to generate risk evaluations. This parameter transformation reduces the complexity of handling raw biological data.
Data Source
AI summary
A technique for calculating a disease evaluation index using intestinal flora is presented. A disease evaluation index calculation method includes a step of inputting one or more diseases that a user wants to be aware of; a step of extracting the user's intestinal flora data, which is a result of analyzing a stool sample of the user in advance, the user's attribute data, and an association model having a plurality of subjects' attribute data, the subjects' intestinal flora data, which is a result of analyzing stool samples of the subjects, and data on the diseases as internal factors, from a database; and a step of calculating a risk of the diseases using the user's intestinal flora data, the user's attribute data, and the association model.