Name
Abstract | ||
|---|---|---|
Over the years, many Artificial Intelligence (AI) approaches have dealt with the diagnosis problem and its application in complex environments such as medical domains. Model-Based Reasoning (MBR) is one of the approaches that traditionally have tried to solve this problem thanks to its capacity for modelling and reasoning. The consideration of the temporal dimension in these domains is a challenging topic in MBR, especially if temporal imprecision is taken into account. Unfortunately, despite there being many successful MBR systems, there are still two fundamental problems in their development at the aforementioned domains: (1) the degree of dependency between the model used and the domain; and (2) the reutilization of the systems when the domain changes. First this paper proposes a set of basic requirements for the design of Knowledge-Based Systems that will help to solve the problem of temporal diagnosis for environments of high conceptual complexity. From these principles and through a deep analysis of the various approaches present in AI we establish a generic framework that addresses both goals by integrating MBR and ontologies for domain knowledge representation in order to describe a intermediate model representation to facilitate the low dependency between the model and the application domain. Finally, this paper demonstrates the use of the framework by developing a diagnosis system within a real medical environment (Intensive Care Unit) with a step-by-step description of the process, from the architecture through to implementation. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.eswa.2007.08.054 | Expert Syst. Appl. |
Keywords | Field | DocType |
application domain,model-based reasoning,successful mbr system,medical domain,domain knowledge representation,diagnosis system,diagnosis problem,aforementioned domain,domain change,temporal diagnosis,intermediate model representation,artificial intelligence in medicine,fundamental problem,computing context-dependent temporal diagnosis,knowledge-based systems,complex domain,domain knowledge,artificial intelligent,context dependent,domain model,model based reasoning,knowledge based system,knowledge based systems | Ontology (information science),Data mining,Architecture,Domain knowledge,Model representation,Computer science,Knowledge-based systems,Model-based reasoning,Artificial intelligence,Application domain,Machine learning | Journal |
Volume | Issue | ISSN |
35 | 3 | Expert Systems With Applications |
Citations | PageRank | References |
12 | 0.73 | 26 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José M. Juarez | 1 | 165 | 19.28 |
| Manuel Campos | 2 | 189 | 20.38 |
| José Palma | 3 | 120 | 14.28 |
| Roque Marín | 4 | 121 | 9.34 |