Evaluating Modelling Approaches for Medical Image Annotations

TL;DR

This paper presents a case study and a conceptual framework for evaluating different modelling approaches for annotating medical images, aiding system designers in selecting suitable semantic technologies.

Contribution

It introduces a novel framework to analyze and compare the effectiveness of various modelling approaches in medical image annotation systems.

Findings

Framework helps identify strengths and weaknesses of modelling approaches.

Assists in managing trade-offs between effort and benefits.

Provides insights into selecting appropriate semantic technologies.

Abstract

Information system designers face many challenges w.r.t. selecting appropriate semantic technologies and deciding on a modelling approach for their system. However, there is no clear methodology yet to evaluate "semantically enriched" information systems. In this paper we present a case study on different modelling approaches for annotating medical images and introduce a conceptual framework that can be used to analyse the fitness of information systems and help designers to spot the strengths and weaknesses of various modelling approaches as well as managing trade-offs between modelling effort and their potential benefits.