{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:37:42Z","timestamp":1740202662601,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"abstract":"<jats:p>Data mining of electronic health records (eHRs) allows us to identify patterns of patient data that characterize diseases and their progress and learn best practices for treatment and diagnosis. Clinical Prediction Rules (CPRs) are a form of clinical evidence that quantifies the contribution of different clinical data to a particular clinical outcome and help clinicians to decide the diagnosis, prognosis or therapeutic conduct for any given patient. The TRANSFoRm diagnostic support system (DSS) is based on the construction of an ontological repository of CPRs for diagnosis prediction in which clinical evidence is expressed using a unified vocabulary. This paper explains the proposed methodology for constructing this CPR repository, addressing algorithms and quality measures for filtering relevant rules. Some preliminary application results are also presented.<\/jats:p>","DOI":"10.3233\/978-1-61499-512-8-85","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:46:46Z","timestamp":1740160006000},"source":"Crossref","is-referenced-by-count":0,"title":["A methodology for mining clinical data: experiences from TRANSFoRm project"],"prefix":"10.3233","author":[{"family":"Danger Roxana","sequence":"additional","affiliation":[]},{"family":"Corrigan Derek","sequence":"additional","affiliation":[]},{"family":"Soler Jean K.","sequence":"additional","affiliation":[]},{"family":"Kazienko Przemyslaw","sequence":"additional","affiliation":[]},{"family":"Kajdanowicz Tomasz","sequence":"additional","affiliation":[]},{"family":"Majeed Azeem","sequence":"additional","affiliation":[]},{"family":"Curcin Vasa","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Digital Healthcare Empowering Europeans"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T18:37:27Z","timestamp":1740163047000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-511-1&spage=85&doi=10.3233\/978-1-61499-512-8-85"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-512-8-85","relation":{},"ISSN":["0926-9630"],"issn-type":[{"value":"0926-9630","type":"print"}],"subject":[],"published":{"date-parts":[[2015]]}}}