Rule-based expert systems

Last revised by Frank Gaillard on 2 May 2019

A rule-based expert system is the simplest form of artificial intelligence and uses prescribed knowledge-based rules to solve a problem 1.  The aim of the expert system is to take knowledge from a human expert and convert this into a number of hardcoded rules to apply to the input data. In their most basic form, the rules are commonly conditional statements (if a, then do x, else if b, then do y). These systems should be applied to smaller problems, as the more complex a system is, the more rules that are required to describe it, and thus increased difficulty to model for all possible outcomes.

Note: with problems related to radiological images, often preprocessing of the images is required prior to the expert system being applied 2.


A very basic example of rule-based expert system would be a programme to direct the management of abdominal aneurysms. The system would input the diameter of an aneurysm. Using conditional arguments, the input diameter would be stratified to recommend whether immediate intervention was required, and if not what appropriate follow up is recommended.

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