Towards an ontological representation of morbidity and mortality in Description Logics

Abstract

BackgroundDespite the high coverage of biomedical ontologies, very few sound definitions of death can be found. Nevertheless, this concept has its relevance in epidemiology, such as for data integration within mortality notification systems. We here introduce an ontological representation of the complex biological qualities and processes that inhere in organisms transitioning from life to death. We further characterize them by causal processes and their temporal borders.ResultsSeveral representational difficulties were faced, mainly regarding kinds of processes with blurred or fiat borders that change their type in a continuous rather than discrete mode. Examples of such hard to grasp concepts are life, death and its relationships with injuries and diseases. We illustrate an iterative optimization of definitions within four versions of the ontology, so as to stress the typical problems encountered in representing complex biological processes. We point out possible solutions for representing concepts related to biological life cycles, preserving identity of participating individuals, i.e. for a patient in transition from life to death. This solution however required the use of extended description logics not yet supported by tools. We also focus on the interdependencies and need to change further parts if one part is changed.ConclusionThe axiomatic definition of mortality we introduce allows the description of biologic processes related to the transition from healthy to diseased or injured, and up to a final death state. Exploiting such definitions embedded into descriptions of pathogen transmissions by arthropod vectors, the complete sequence of infection and disease processes can be described, starting from the inoculation of a pathogen by a vector, until the death of an individual, preserving the identity of the patient.

The Drosophila phenotype ontology

“…The only other ontological framework for recording mortality rates that we are currently aware of, an impressively detailed and well-axiomatised proposal from Sanatana and colleages [ 29 ], is not suited to our needs: it is based on a different upper ontology to the DPO; it assumes that death is due to injury or disease; and it does not include axioms for reasoning about relative timings.…”

Information science ontologies and metaphysics: In regard to an umbrella protocol for standardized data collection in rectal cancer by Meldolesi et al.

“…For example, if a ''pathological complete remission'' (PCR) rate of 17% is ascribed to rectal cancer treated with neoadjuvant chemoradiation then this is not a property inhering in any individual of ''rectal cancer'' or ''neoadjuvant treatment'', it is rather a factual statement that cannot be straightforwardly represented in formal ontologies using OWL. The task of knowledge representation would be more complicated for those processes with diffuse border that chronically change their type in per continuitatem rather than discrete mode such as ''quality of life'', ''morbidity'' and ''mortality'' [6]. For artificial intelligence systems, what ''exists'' is that which can be represented [7].…”