Dirk Marwede | PubMed Health

PubMed2006

Four ontological models for radiological diagnostics.

In this paper we isolate four diagnostic models in radiology and define a set of diagnostic relations corresponding to each clinical situation. To achieve this, we describe a set of general formal ontological notions, as well as the ontological model of the imaging domain we employed in our analysis. On the basis of our results, we conclude that these diagnostic models and the relations contained therein could be applied to diagnostic situations outside of radiology as well.

Germany↗

PubMed2005

An ontology for carcinoma classification for clinical bioinformatics.

There are a plenty of existing classifications and staging schemes for carcinomas, one of the most frequently used being the TNM classification. Such classifications involve entities which exist at various anatomical levels of granularity and in order to apply such classifications to the Electronic Health Care Records, one needs to build ontologies which are not only based on the formal principles but also take into consideration the diversity of the domains which are involved in clinical bioinformatics. Here we outline a formal theory for addressing these issues in a way that inferences drawn upon the ontologies would be helpful in interpreting and inferring on the entities which exist at different anatomical levels of granularity. Our case study is on the colon carcinoma, one of the commonest carcinomas prevalent within the European population.

Computational Biology↗

PubMed2005

The epistemological-ontological divide in clinical radiology.

Medical ontologies like GALEN, the FMA or SNOMED represent a kind of "100% certain" medical knowledge which is not inherent to all medical sub-domains. Clinical radiology uses computerized imaging techniques to make the human body visible and interprets the imaging findings in a clinical context delivering a textual report. For clinical radiology few standardized vocabularies are available. We examined the definitions given in the glossary of terms for thoracic radiology published by the Fleischner Society. We further classified these terms with regard to their definitions in terms of (a) describing visible structures on the image itself, (b) referring to ontological entities of the body (anatomical or pathological), and (c) terms imposing knowledge on structures visible on the image, epistemologically representing ontological entities of the body. Each ontological/epistemological definition was rated on a scale of vague/weak-sound/strong and put in context with the evaluation comments for the use of the terms given in the glossary itself. The result of this distinction shows that clinical radiology uses many terms referring to ontological entities valid for representation in a medical ontology. However, many epistemological terms exist in the terminology which impose epistemological knowledge on ontological entities. The analysis of the evaluation comments reveals that terms classified as sound (ontologically) and strong (epistemologically) are evaluated higher than terms bearing vague or weak definitions. On the basis of this, we argue that the distinction between ontological and epistemological definitions is necessary in order to construct epistemologically-sensitive application ontologies for medical sub-domains, like clinical radiology, where knowledge is fragmented in terms of description, inferred from a description, concluded on the basis of imaging, or other additional information with varying degrees of certainty.

Electronic Data Processing↗