Integration of Rule Based Expert Systems and Case Based Reasoning in an Acute Bacterial Meningitis Clinical Decision Support System

TL;DR

This paper presents a clinical decision support system for Acute Bacterial Meningitis that integrates Case Based Reasoning with Rule Based Expert Systems, focusing on the adaptation stage to improve diagnostic accuracy.

Contribution

It introduces a novel integration of CBR and rule-based systems with a higher-level RBC for better adaptation in medical diagnosis.

Findings

Enhanced diagnostic decision support for meningitis

Effective integration of CBR and rule-based systems

Pre-diagnosis rule engine streamlines process

Abstract

This article presents the results of the research carried out on the development of a medical diagnostic system applied to the Acute Bacterial Meningitis, using the Case Based Reasoning methodology. The research was focused on the implementation of the adaptation stage, from the integration of Case Based Reasoning and Rule Based Expert Systems. In this adaptation stage we use a higher level RBC that stores and allows reutilizing change experiences, combined with a classic rule-based inference engine. In order to take into account the most evident clinical situation, a pre-diagnosis stage is implemented using a rule engine that, given an evident situation, emits the corresponding diagnosis and avoids the complete process.