An ontological-based monitoring system for patients with bipolar I disorder
Our aim is to provide a patient monitoring system that integrates a Clinical Decision Support System (CDSS) and an Electronic Health Record (EHR) that assist psychiatrists and primary care physicians to tackle existent health needs of mental illness related to the treatment and management of bipolar I disorder (BDI). Our monitoring system consists of an EHR system based on the Health Level Seven Reference Information Model (HL7-RIM) and an ontological-based CDSS leveraging the Semantic Web capabilities. Based on the evidence-based clinical guidelines and patients’ health records, the monitoring system is developed to encode and process this information and subsequently to assign recommendations of choices and alerts to clinicians for improved mental health care. Considering the clinical guidelines germane knowledge, as well as issues of patient’s health record, the monitoring system can support a personalized decision-making for bipolar I disorder longitudinal course. We propose AI-CARE as an online monitoring tool that may offer useful guidance in clinical practice.
About Authors (Correspondence):
Thermolia Ch.H. – student, the Intelligent Systems Laboratory, e-mail: cthermolia@ intelligence.tuc.gr
Bei E.S. – Ph.D., postdoctoral researcher, the Intelligent Systems Laboratory, e-mail: firstname.lastname@example.org
Petrakis E.G.M. – Ph.D., Professor, laboratory director, the Intelligent Systems Laboratory, e-mail: email@example.com
Kritsotakis V. – M.Sc., technical staff, Computational BioMedicine Laboratory, e-mail: firstname.lastname@example.org
Sakkalis V. – Ph.D., principal researcher, Computational BioMedicine Laboratory, e-mail: email@example.com