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An ontological-based monitoring system for patients with bipolar I disorder

Petrakis Evripidis, Bei Aikaterini, Thermolia Chryso, Vangelis Kritsotakis, Vangelis Sakkalis

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URI: http://purl.tuc.gr/dl/dias/3296C754-3796-4E2A-A004-C2C983FC13F3
Year 2015
Type of Item Conference Paper Abstract
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Bibliographic Citation Chryssa Thermolia, Ekaterini S. Bei, Euripides G.M. Petrakis, Vangelis Kritsotakis, Vangelis Sakkalis. (2015, Oct.).An Ontological-Based Monitoring System for Patients with Bipolar I Disorder. Presented at International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON). [Online]. Available: http://www.intelligence.tuc.gr/~petrakis/publications/SIBIRCON2015.pdf
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Summary

Our aim is to provide a patient monitoring systemthat integrates a Clinical Decision Support System (CDSS) andan Electronic Health Record (EHR) that assist psychiatrists andprimary care physicians to tackle existent health needs of mentalillness related to the treatment and management of bipolar Idisorder (BDI). Our monitoring system consists of an EHRsystem based on the Health Level Seven Reference InformationModel (HL7-RIM) and an ontological-based CDSS leveraging theSemantic Web capabilities. Based on the evidence-based clinicalguidelines and patients’ health records, the monitoring system isdeveloped to encode and process this information andsubsequently to assign recommendations of choices and alerts toclinicians for improved mental health care. Considering theclinical guidelines germane knowledge, as well as issues ofpatient’s health record, the monitoring system can support apersonalized decision-making for bipolar I disorder longitudinalcourse. We propose AI-CARE as an online monitoring tool thatmay offer useful guidance in clinical practice.

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