Can an Ad-hoc ontology Beat a Medical Search Engine? The Chronious Search Engine case

TL;DR

This paper presents a novel ontology-based literature search engine within the Chronious platform for chronic disease management, demonstrating its superior performance over traditional web search engines in specific estimation parameters.

Contribution

It introduces an ontology-based search engine integrated into a comprehensive chronic disease management platform, showing improved search effectiveness over standard web search methods.

Findings

Ontology search engine outperforms web search in key parameters

Effective integration of ontology with decision support and sensors

Enhanced clinician decision-making support

Abstract

Chronious is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD) Chronic Kidney Disease (CKD) and Renal Insufficiency. It consists of several modules: an ontology based literature search engine, a rule based decision support system, remote sensors interacting with lifestyle interfaces (PDA, monitor touch-screen) and a machine learning module. All these modules interact each other to allow the monitoring of two types of chronic diseases and to help clinician in taking decision for care purpose. This paper illustrates how the ontology search engine was created and fed and how some comparative test indicated that the ontology based approach give better results, on some estimation parameters, than the main reference web search engine.