Medical Knowledge Representation in Terms of IF-THEN Rules and the Dempster-Shafer Theory

Straszecka, Ewa

doi:10.1007/978-3-540-24844-6_165

Cited by 6 publications

(3 citation statements)

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“…However, it receives some criticism concerning the computational complexity that generates for large sets of hypotheses (Clark 1990). Despite these shortcomings, Dempster-Shaffer Theory has been used efficiently for the representation of medical knowledge and uncertainty in some critical areas (Straszecka 2004).…”

Section: Reasoning Under Uncertaintymentioning

confidence: 99%

Development and implementation of clinical guidelines: An artificial intelligence perspective

2013

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Clinical Practice Guidelines in paper format are still the preferred form of delivery of medical knowledge and recommendations to healthcare professionals. Their current support and development process have well identified limitations to which the healthcare community has been continuously searching solutions. Artificial Intelligence may create the conditions and provide the tools to address many, if not all, of these limitations.. This paper presents a comprehensive and up to date review of Computer-Interpretable Guideline approaches, namely Arden Syntax, GLIF, PROforma, Asbru, GLARE and SAGE. It also provides an assessment of how well these approaches respond to the challenges posed by paper-based guidelines and addresses topics of Artificial Intelligence that could provide a solution to the shortcomings of clinical guidelines. Among the topics addressed by this paper are Expert Systems, Case-Based Reasoning, Medical Ontologies and Reasoning under Uncertainty, with a special focus on methodologies for assessing Quality of Information when managing incomplete information. Finally, an analysis is made of the fundamental requirements of a guideline model and the importance that standard terminologies and models for clinical data have in the semantic and syntactic interoperability between a 1 Corresponding author 2 guideline execution engine and the software tools used in clinical settings. It is also proposed a line of research that includes the development of an ontology for Clinical Practice Guidelines and a decision model for a guideline-based Expert System that manages non-compliance with clinical guidelines and uncertainty

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Section: Reasoning Under Uncertaintymentioning

confidence: 99%

Development and implementation of clinical guidelines: An artificial intelligence perspective

2013

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“…This kind of hybridization is generally accepted in medical settings, since easily usable and understandable also by a non-technical audience [16,32]. As a result, applying the patterns defined in the previous section within a hybrid KB, made of if-then rules built on the top of ontological vocabularies, has appeared the more suitable solution to simplify the formalization of a very complex kind of knowledge, such as the medical one.…”

Section: Pattern Instantiation Within Hybrid Knowledge Basesmentioning

confidence: 97%

A pattern-based knowledge editing system for building clinical Decision Support Systems

Minutolo

Esposito

Pietro

2012

Knowledge-Based Systems

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“…the structure of the domain knowledge) in form of ontology-based models, whereas procedural knowledge (i.e. the knowledge about the decision making process) as a set of if-then rules built on the top of such models, according to the awareness that the combination of more representation techniques frequently perform better than the individual ones (Arguello Casteleiro et al, 2009;Kong et al, 2008;Straszecka, 2004;Ting et al, 2011).…”

Section: Background On Light-weight Knowledge Representation and Reasmentioning

confidence: 99%

Design and validation of a light-weight reasoning system to support remote health monitoring applications

Minutolo

Esposito

Pietro

2015

Engineering Applications of Artificial Intelligence

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Medical Knowledge Representation in Terms of IF-THEN Rules and the Dempster-Shafer Theory

Cited by 6 publications

References 1 publication

Development and implementation of clinical guidelines: An artificial intelligence perspective

Development and implementation of clinical guidelines: An artificial intelligence perspective

A pattern-based knowledge editing system for building clinical Decision Support Systems

Design and validation of a light-weight reasoning system to support remote health monitoring applications

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