Temporal Medical Knowledge Representation Using Ontologies

Jacques Hilbey (1, 2) , Xavier Aimé (1) , Jean Charlet (1, 3)

1 LIMICS - Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé
2 SU - Sorbonne Université
3 AP-HP - Assistance publique - Hôpitaux de Paris (AP-HP)

Representing temporal information is a recurrent problem for biomedical ontologies. We propose a foundational ontology that combines the so-called threedimensional and four-dimensional approaches in order to be able to track changes in an individual and to trace his or her medical history. This requires, on the one hand, associating with any representation of an individual the representation of his or her life course and, on the other hand, distinguishing the properties that characterize this individual from those that characterize his or her life course.

Mots clés: Knowledge representation; biomedical ontologies; temporal representation; historical aspects

Domaines: Informatique [cs]

Jacques Hilbey, Xavier Aimé, Jean Charlet. Temporal Medical Knowledge Representation Using Ontologies. Challenges of Trustable AI and Added-Value on Health, IOS Press, 2022, Studies in Health Technology and Informatics, ⟨10.3233/shti220470⟩. ⟨hal-03683532⟩