Incremental Rule Evaluation for Medical Diagnosis Systems
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Solution Overview
Problem
Conventional rule-based systems assume all inputs are available at the time of evaluation, which can be costly and inefficient, especially in applications like medical diagnosis where not all telemetry is readily available.
Innovation Solution
Incremental rule condition evaluation reduces the ruleset by determining the value of input conditions at evaluation time, allowing for a subset of rules to be evaluated based on known inputs, thereby minimizing testing and telemetry collection costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all inputs are made available at the point of rule condition evaluation, then the completeness of rule evaluation is improved, but the cost of data collection and processing increases
Solution Approach 1:
The system performs preliminary actions by collecting and storing input data before rule evaluation is needed. Data collection occurs in advance during normal system operation, so when rule evaluation is triggered, the data is already available without requiring additional costly collection efforts.
Solution Approach 2:
The system creates copies of input data and stores them in a data structure for later use. Instead of re-collecting data during rule evaluation, the system uses pre-collected copies of the data, reducing the cost of data collection while maintaining evaluation completeness.
2Measurement precision
If all inputs are collected before rule evaluation, then the accuracy of rule firing determination is improved, but the time required for evaluation increases
Solution Approach 1:
The system performs preliminary data collection and organization before rule evaluation is needed. By having data ready in advance and organizing it in an efficient data structure, the system eliminates delays during the actual evaluation process while ensuring all necessary inputs are available for accurate rule firing determination.
3Reliability
If the complete ruleset is evaluated, then the comprehensiveness of diagnosis is improved, but the processing efficiency decreases
Solution Approach 1:
The system extracts and evaluates only the relevant subset of rules based on currently available input data. By identifying which rules can be evaluated with existing data and separating them from rules requiring additional data, the system maintains diagnostic comprehensiveness for evaluable rules while improving processing efficiency by avoiding unnecessary rule evaluations.
Data Source
AI summary
A first ruleset associated with a rule-based system is received. Incremental rule evaluation is performed, wherein not all input values are known at the start of rule evaluation, at least in part by: selecting a first input for which to determine a first new value; determining the first new value; and determining a second ruleset by removing from the first ruleset rules whose rule condition can no longer be true based on the first input value.