Ontology Patterns for Clinical Information Modelling

In this section, we suggest three extensions to the current state of the art, namely: intro- ducing new temporal relations for the construction of semantic health graphs; a flexible

Having an XML schema, X2OWL can automatically generate an OWL ontology from this schema. This process is based on some mapping rules that indicates how to convert each com- ponent

A major barrier to repurposing clinical data directly from Electronic Health Records (EHRs) or from Clinical Data Warehouses (CDWs) during clinical trial design and

The EHR-Based Query Generation module deals with electronic health record information, extracting the most relevant features regarding specific pathologies.. These characteristics

The desired knowledge structures to be extracted from EHRs can be grouped in the following types: (i) Characteristics for filling information in templates for patient status,

The four main levels involved in the approach consist of: (1) the construction of a domain ontology of design and manufacture hole features whose definitions

It is then introduced an Information Retrieval algorithm that allows to derive a unique path among the entities involved in the query in order to obtain maxima semantic associations

Dimensions of an ontology use can be identified as (1) role, (i.e., the way the ontology is used); (2) justification (addressing whether A is entitled for using M in role R because M