AI-CARE: Advanced Knowledge Management Systems with Inherence Computational Intelligence and Applications in Health Care
Contract Details
Programme Acronym:
Contract No:
Start Date: 2012-10-19
End Date: 2015-06-30
Project Status: execution
Budget for TUC: 126,000 euros
Role for TUC: prime
Principal Investigator for TUC: Euripides G.Μ. Petrakis
Project Description

Bipolar disorder (BPD) is one of the most severe forms of mental illness, characterized by mood swings and is ranked as sixth cause of disability worldwide for individuals between the ages of 14 and 44. It is a frequent and often chronic psychiatric disease thought to be caused by an interaction of genetic and environmental factors. The condition is triggered by stressful life events, is often misdiagnosed and/or not adequately treated, and is associated with an increased risk of suicide. Long-term pharmacologic treatment is indicated early in the course of the illness to prevent recurrence, suicidal behaviour, and chronicity. On the other hand, Epilepsy is one of the most common neurological disorders characterized by recurrent and usually unpredictable seizures, with a prevalence of 0.6â8% of the worldâpopulation. I It is a dynamical disease of the brain affecting about 3% to 5% of the population at some time in life. Anticonvulsive medication and epilepsy surgery offers symptoms free disease (seizure freedom) to the majority of patients with epilepsy but still for a remaining 25% of patients, no sufficient treatment is currently available. Bipolar disorder and epilepsy share some aspects of biochemical and pathophysiological underpinnings, such as the kindling phenomenon, changes in neurotransmitters and modifications in voltage-opened ion channels and second messenger systems. Additionally, epilepsy and bipolar disorders are both episodic conditions with a time course of illness that can become chronic.

The AI-CARE project is expected to provide answers to relevant questions related to bipolar disorder and epilepsy issues, such as the individualization of diagnosis, treatment approaches and effectiveness of treatment, quality of life, transition hazard from major depressive episodes to manic, hypomanic, or mixed states, malignant types of bipolar disorder, psychiatric disturbances and suicide risk after epilepsy surgery and high risk patients with epilepsy. Computer assisted medical care has generated additional interest in methods and tools for the management, analysis, and communication of medical information. In this regard, archives of medical (patient) records can be used for supporting administrative, clinical and research activities. Building upon state-of-the-art in information systems development, model building and semantic technology research (OWL-family of ontology languages, temporal reasoning, temporal databases, natural language processing) the project will develop a model capable to extract and utilize validated information from Health sources exploiting semantic technology in the medical domain. The system will interpret patient information extracted from patient records through rule-based and statistical validation and will validate the effect of suggested treatment or diagnosis on the cause, progression and eventually treatment of epilepsy and bipolar diseases.

AI-CARE targets a specific research domain in a sharply focused approach while at the same time it includes a coherent and integrated set of activities dealing with multiple related issues and provides state-of-the-art responses to the identified challenges. Special emphasis is given in making sure that the new tools, services and applications to be developed in AI-CARE will also be evaluated on their effectiveness and validated in use cases with a high potential for improving patient management and safety. In order to build, verify and demonstrate the proposed solutions, a suitable consortium has been built, which contains relevant partners from research organisations, as well as clinical specialised SMEs with significant expertise and intensions to exploit project results. The project consortium consists of the research organisations TSI (Telecommunication Systems Institute, Technical University of Crete) and CML-FORTH (Computational Medicine Laboratory, Institute of Computer Science FORTH) and the private healthcare facility SMEs NCPD (Neurofeedback Centre for Psychophysiological Development) and EUROMEDIC.

AI-CARE project is funded by the National Strategic Reference Framework (NSRF) 2007 -2013, "Action Cooperation 2011" of the Hellenic Ministry of Development and General Secretariat for Research & Technology.

Official Project Web Site:
Related Publications
  • Thermolia C., Bei K., Petrakis E., Kritsotakis V., Tsiknakis M., Sakkalis V.: Designing A Patient Monitoring System for Bipolar Disorder Using Semantic Web Technologies, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2015), Milan, Italy, August 25-29, 2015.
    Publication Type: Conference Publications [abstract] [file]
  • Thermolia C., Bei K., Sotiriadis S., Stravoskoufos K., Petrakis E.: Designing A Patient Monitoring System Using Cloud And Semantic Web Technologies, 17th International Conference on Brain and Health Informatics (ICBHI 2015), London, UK, May 25-26 2015 (presentation).
    Publication Type: Conference Publications [abstract] [file]
  • Thermolia C., Bei K., Petrakis E.: Prediction of the Evolution of Bipolar Depression using Semantic Web Technologies, 5th International Conference on Information, Intelligence, Systems and Applications (IISA 2014), Chania, Crete, Greece, July 7-9 2014.
    Publication Type: Conference Publications [abstract] [file]
  • Thermolia C., Bei K., Petrakis E.: TeleCare of Mental Disorders by Applying Semantic Web Technology, IEEE 13th International Conference on Bioinformatics and Bioengineering, (BIBE 2013), November, 10-13, 2013, Chania, Crete.
    Publication Type: Conference Publications [abstract] [file]
Project Consortium
EEG Biofeedback
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