Integrating Medical Scientific Knowledge with the Semantically Quantified Self
- Submitting institution
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The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1453472
- Type
- E - Conference contribution
- DOI
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10.1007/978-3-319-46523-4_34
- Title of conference / published proceedings
- 15th International Semantic Web Conference, ISWC 2016
- First page
- 566
- Volume
- 9981
- Issue
- -
- ISSN
- 0302-9743
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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7
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper describes an ontology and architecture for semantically integrating individual health data with a knowledge base of clinical risk factors for personalised prediction. The work was initially applied in clinical trials with 98 at-risk or diagnosed cardiorenal patients in Greece and Lithuania, improving: health literacy (21.3% for diagnosed patients) and patient empowerment (12.4% for at risk patients). Directly because of this work, exercises were added to an OU sports module with every student receiving a fitness tracker and ability to carry out self-data analysis using our platform (1707 students over 4 years). ISWC research track: 18% acceptance. Funding https://www.carre-project.eu/.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -