Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/iswc2013/poster-demo-proceedings/paper-16> ?p ?o. }
Showing items 1 to 7 of
7
with 100 items per page.
- paper-16 type InProceedings.
- paper-16 label "Using Ontologies to Identify Patients with Diabetes in Electronic Health Records".
- paper-16 sameAs paper-16.
- paper-16 abstract "This paper describes a work in progress that explores the applicability of ontology for providing solutions in medical domain. We investigate whether it is feasible to use ontologies and ontology-based data access to automate one of common clinical tasks that are constantly faced by general practitioners but labor intensive and error prone in term of relevant information retrieved from electronic health records. The focus of our study is on improving diabetes patient selection for clinical trials or medical research. The biggest impediment to automating such clinical tasks is the essential requirement of bridging the semantic gaps between existing patient data from electronic health records, such as reasons for visit, chronic conditions and diagnoses from practice notes, pathology tests and prescriptions stored in general practice information systems, and the ways which researchers or general practitioners interpret those records. Our current comprehension is that automation of identifying diabetes patients for clinical or research purposes can be specified systematically as a solution supported by semantic retrieval. We detail the challenges to build a realistic case study, which consists of solving issues related to conceptualization of data and domain context, integration of different datasets, ontology creation based on SNOMED CT-AU® standard, mapping between existing data and ontology, and dilemma of data fitness for research use. Our prototype is based on data which scale to thirteen years of approximate 100,000 anonymous patient records from four general practices in south western Sydney.".
- paper-16 hasAuthorList authorList.
- paper-16 isPartOf poster-demo-proceedings.
- paper-16 title "Using Ontologies to Identify Patients with Diabetes in Electronic Health Records".