Student engagement is an important factor for learning outcomes in higher education. Engagement with learning at campus-based higher education institutions is difficult to quantify due to the variety of forms that engagement might take (e.g.
View Article and Find Full Text PDFClinical Decision Support (CDS) systems hold tremendous potential for improving patient care. Most existing systems are knowledge-based tools that rely on relatively simple rules. More recent approaches rely on analytics techniques to automatically mine EHR data to reveal meaningful insights.
View Article and Find Full Text PDFStud Health Technol Inform
January 2013
The personalized medicine era stresses a growing need to combine evidence-based medicine with case based reasoning in order to improve the care process. To address this need we suggest a framework to generate multi-tiered statistical structures we call Evicases. Evicase integrates established medical evidence together with patient cases from the bedside.
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December 2011
Existing Clinical Decision Support Systems (CDSSs) typically rely on rule-based algorithms and focus on tasks like guidelines adherence and drug prescribing and monitoring. However, the increasing dominance of Electronic Health Record technologies and personalized medicine suggest great potential for prognostic data-driven CDSS. A major goal for such systems would be to accurately predict the outcome of patients' candidate treatments by statistical analysis of the clinical data stored at a Health Care Organization.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
April 2010
One of the challenges of healthcare data processing, analysis and warehousing is the integration of data gathered from disparate and diverse data sources. Promoting the adoption of worldwide accepted information standards along with common terminologies and the use of technologies derived from semantic web representation, is a suitable path to achieve that. To that end, the HL7 V3 Reference Information Model (RIM) [1] has been used as the underlying information model coupled with the Web Ontology Language (OWL) [2] as the semantic data integration technology.
View Article and Find Full Text PDFGene structure prediction is one of the most important problems in computational molecular biology. It involves two steps: the first is finding the evidence (e.g.
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