Expert Systems

An expert system is a computer program that replicates the decision-making ability of a human specialist in a specific domain. It has two core components. The knowledge base stores domain facts and rules, typically as if-then statements written by human experts. The inference engine interprets those rules to reach conclusions, handling uncertainty, partial information, and complex logical chains.

Expert systems were the dominant AI architecture in the 1980s and remain useful today. In healthcare, they flag potential drug interactions and suggest diagnostic tests. In finance, they evaluate credit risk and detect fraud. In manufacturing, they guide troubleshooting of complex machinery.

The knowledge base can be updated as new research appears, so the system stays current without a full software rebuild. Expert systems are less flexible than modern neural networks but far more interpretable, since every recommendation comes with a traceable chain of reasoning.

Interactive Visualizer

Interactive medical diagnosis system showing knowledge base and inference engine

Patient Cases

Patient A

fever: 39°C, headache, fatigue

Patient B

chest pain, shortness of breath, sweating

Patient C

skin rash, fever: 38.5°C, body aches

Knowledge Base

Rule 1

IF fever > 38°C AND headache THEN check for infection

Rule 2

IF chest_pain AND shortness_of_breath THEN cardiac_concern

Rule 3

IF rash AND fever THEN viral_infection_likely

Rule 4

IF viral_infection_likely THEN prescribe_rest_and_fluids

Inference Engine

Select a patient case to start diagnosis