Vaccine Recommendation Inference Engine Logic
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Solution Overview
Problem
Current computer systems for vaccine recommendations face challenges in complexity, including contradictory recommendations, difficulty in updating rules, and inability to handle multiple vaccine names, making it hard for both professionals and users to understand and apply vaccination guidelines effectively.
Innovation Solution
A computer-based vaccine recommendation method that uses a digital interface to supply health data, an inference engine to determine personalized recommendations, and allows easy updating of vaccination rules, ensuring non-contradictory and relevant advice through a logical formula-based system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If vaccination rules are encoded in a complex algorithmic system, then the system can provide vaccination recommendations, but the system produces contradictory recommendations and becomes difficult to update
Solution Approach 1:
The patent segments the vaccination recommendation system into distinct modules: a knowledge base storing vaccination rules in a structured format (e.g., RDF triples), an inference engine for logical reasoning, and a user interface. This segmentation allows each component to be independently updated and maintained, reducing contradictions and improving reliability while maintaining automation.
2Reliability
If vaccination rules are hard-coded in the system, then the system provides robust recommendations, but updating rules requires software rewriting and IT expertise
Solution Approach 1:
The patent introduces an intermediary layer between the raw vaccination rules and the system logic: a structured knowledge base using standardized formats (e.g., RDF, ontologies). This intermediary allows vaccination experts to update rules by modifying data in the knowledge base without requiring software rewriting, while the inference engine maintains reliable processing of these rules.
3Adaptability or versatility
If the system uses multiple vaccine names and variations, then the system covers more vaccine types, but the system cannot recognize and process common names for the same vaccine
Solution Approach 1:
The patent implements a universal identifier system and ontology that maps multiple vaccine names and variations to a single standardized representation. The knowledge base stores relationships between different names (synonyms, brand names, generic names) and the standardized vaccine entity, enabling the system to recognize and process common names for the same vaccine while maintaining comprehensive coverage.
4Reliability
If vaccination guidelines are made detailed and comprehensive, then the benefit-risk ratio is maximized, but it becomes increasingly difficult to understand and correctly apply recommendations
Solution Approach 1:
The patent implements a system where the inference engine automatically applies the detailed vaccination rules to the user's specific health data and vaccination history, generating personalized recommendations without requiring the user or healthcare professional to manually interpret complex guidelines. The system handles the complexity internally while presenting simplified, actionable recommendations to users.
Data Source
Figure 1~2
AI summary
The invention relates to a vaccination recommendation method (1), implemented by a computer system (2) comprising a set of vaccination rules (VS1) and at least one digital interface (NT1), comprising the following steps: provision of at least one set of health data of at least one person by means of said digital interface (NT1); determination of at least one set of vaccination recommendations by an inference engine (IM1) from said set of health data provided and said set of vaccination rules (VS1); transmission of said set of recommendations on said digital interface (NT1).