title: Addressing the challenge of encoding causal epidemiological knowledge in formal ontologies: a practical perspective.
abstract: The paper presents an overview of approaches to encoding uncertain causal knowledge in formal ontologies and demonstrates how these approaches can be used in a semantic-driven application for public health using the Population Health Record (PopHR) platform as an example.
authors.affiliation: McGill University Clinical and Health Informatics Research Group.
authors.forename: Anya
authors.initials: A
authors.lastname: Okhmatovskaia
authors.affiliation: McGill University Clinical and Health Informatics Research Group.
authors.forename: Arash
authors.initials: A
authors.lastname: Shaban-Nejad
authors.affiliation: McGill University Clinical and Health Informatics Research Group.
authors.forename: Maxime
authors.initials: M
authors.lastname: Lavigne
authors.affiliation: McGill University Clinical and Health Informatics Research Group.
authors.forename: David L
authors.initials: DL
authors.lastname: Buckeridge
mesh_terms: D064229:Biological Ontologies / Q000458:organization & administration* / Q000706:statistics & numerical data; D015984:Causality; D057286:Electronic Health Records / Q000458:organization & administration*; D004812:Epidemiologic Methods; D006304:Health Status; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008498:Medical Record Linkage / Q000379:methods*; D009323:Natural Language Processing; D012660:Semantics; D018875:Vocabulary, Controlled