Fundus Image Risk Estimation with Biological Data Correction
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Solution Overview
Problem
Existing methods for disease risk determination using biological images and ophthalmic examination equipment suffer from insufficient accuracy.
Innovation Solution
An information processing apparatus that obtains fundus images and biological information, uses a learned model to estimate disease risk, and corrects the estimation using weight coefficients based on biological information to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only biological images from diagnostic imaging equipment or ophthalmic examination equipment are used for disease risk determination, then the examination process is simple, but the determination accuracy is insufficient
Solution Approach 1:
The patent combines multiple data sources including biological images from diagnostic imaging equipment, biological images from ophthalmic examination equipment, and biological information from other examinations into a unified disease risk determination system. This integration allows the system to leverage diverse data types to improve determination accuracy while maintaining a coordinated approach to data collection and processing
2Measurement precision
If multiple types of data including biological images and biological information are integrated for disease risk determination, then the determination accuracy is improved, but the data processing complexity increases
Solution Approach 1:
The patent employs a learned model that can process multiple types of input data including biological images and biological information through a unified processing framework. This multi-functional approach allows the system to handle diverse data types consistently, improving determination accuracy while managing processing complexity through standardized procedures
Solution Approach 2:
The learned model serves as an intermediary that processes and integrates multiple data sources before producing disease risk determination results. This intermediary component coordinates the processing of biological images and biological information, transforming diverse inputs into a unified risk assessment while managing the complexity of data integration
Data Source
AI summary
An information processing apparatus disclosed in the present specification includes: estimation means for estimating a subject's risk of developing a disease using a learned model that has learned a relationship between a feature obtained from a fundus image and a risk of developing the disease, which is evaluated from the feature; and correction means for correcting the estimated risk of developing the disease based on the subject's biological information.