Modern and integrated techniques for medical information management, interfaces, interaction and medical decision support systems

Course Information
TitleΣύγχρονες και ολοκληρωμένες τεχνικές διαχείρισης ιατρικής πληροφορίας, διεπαφές, διάδραση και συστήματα στήριξης αποφάσεων / Modern and integrated techniques for medical information management, interfaces, interaction and medical decision support systems
Interdepartmental ProgrammeIPPS "Medical Informatics" (2019-today)
Collaborating SchoolsMedicine
Electrical and Computer Engineering
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter
CoordinatorDimitrios Zarpalas
Course ID600004411

Programme of Study: IPPS "Medical Informatics" (2019-today)

Registered students: 0
OrientationAttendance TypeSemesterYearECTS
KORMOSCompulsory Course328

Class Information
Academic Year2018 – 2019
Class PeriodWinter
Faculty Instructors
Instructors from Other Categories
Weekly Hours2
Class ID
Course Type 2016-2020
  • Scientific Area
  • Skills Development
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Language of Instruction
  • Greek (Instruction, Examination)
Required Courses
  • ΙΠΑ001 Functional systems anatomy and morphology
  • ΙΠΑ002 Systems Physiology
  • ΙΠΑ004 Mathematics, programming techniques and design principles of medical information systems
  • ΙΠΒ001 Bio-data and applications - Bioinformatics
  • ΙΠΒ004 Biomedical signal processing
  • ΙΠΒ003 Biomedical image processing
  • ΙΠΒ002 Networks and Internets
General Prerequisites
The graduate students should have finalized all courses from the previous two semesters since they need a combination of knowledge in biodata management and analytics, ICT for health and physiology and functional morphology for medical decision making.
Learning Outcomes
It is expected that the graduate students shall be able to develop, manage, evaluate and integrate eHealth systems with major emphasis on advanced data analytics and information management, medical decision support systems, large-scale computing systems based on semantic technologies and agent-based computing, pervasive health and personal health systems.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an international context
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Design and manage projects
  • Advance free, creative and causative thinking
eHealth, medical decision support systems, pervasive health systems, biomedical information processing and management, semantic technologies, agent-based systems, processing of unstructured data
Educational Material Types
  • Notes
  • Slide presentations
  • Multimedia
  • Interactive excersises
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Course Organization
Written assigments301
Student Assessment
Individual project presentation and assessment of project deliverables (paper, software code, etc. depending on the project case).
Student Assessment methods
  • Written Assignment (Summative)
  • Oral Exams (Summative)
  • Design and/or implementation of software (Summative)
Course Bibliography (Eudoxus)
Μη διαθέσιμη. Οι παρουσιάσεις συνοδεύονται από σύγχρονες βιβλιογραφικές πηγές όπως review paper, case studies και tutorial (βλπ. β. Επιπρόσθετη βιβλιογραφία για μελέτη).
Additional bibliography for study
P. Natsiavas, J. Rasmussen, M. Voss-Knude, Κ. Votis, L. Coppolino, P. Campegiani, I. Cano, D. Marí, G. Faiella, F. Clemente, M. Nalin, E. Grivas, O. Stan, E. Gelenbe, J. Dumortier, J. Petersen, D. Tzovaras, L. Romano, I. Komnios and V. Koutkias, “Comprehensive user requirements engineering methodology for secure and interoperable health data exchange”, BMC Medical Informatics and Decision Making, 2018, M. Staffa, L. Sgaglione, G. Mazzeo, L. Coppolino, S. D'Antonio, L. Romano, E. Gelenbe, O. Stan, S. Carpov, E. Grivas, P. Campegiani, L. Castaldo, K. Votis, V. Koutkias, and I. Komnios, “An OpenNCP-based Solution for Secure eHealth Data Exchange”, Journal of Network and Computer Applications, vol. 116, no. 15, 2018, pp. 65–85, P. Natsiavas, R.D. Boyce, M.-C. Jaulent, and V. Koutkias, “OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies”, Frontiers in Pharmacology, 2018, V.G. Koutkias, A. Lillo-Le Louët and M.-C. Jaulent, "Exploiting Heterogeneous Publicly Available Data Sources for Drug Safety Surveillance: Computational Framework and Case Studies", Expert Opinion on Drug Safety, 2016, V.G. Koutkias and M.-C. Jaulent, "A Multiagent System for Integrated Detection of Pharmacovigilance Signals", Journal of Medical Systems, Special Issue on Agent-Empowered HealthCare Systems, vol. 40, no. 2, Article: 37, 2016, V.G. Koutkias and M.-C. Jaulent, "Computational Approaches for Pharmacovigilance Signal Detection: Toward Integrated and Semantically-enriched Frameworks", Drug Safety, vol. 38, no. 3, 2015, pp. 219-232, V.G. Koutkias et al., "From Adverse Drug Event Detection to Prevention: A Novel Clinical Decision Support Framework for Medication Safety", Methods of Information in Medicine, vol. 53, no. 6, 2014, pp. 482-492, V. Koutkias et al., "Knowledge Engineering for Adverse Drug Event Prevention: On the Design and Development of a Uniform, Contextualized and Sustainable Knowledge-based Framework", Journal of Biomedical Informatics, vol. 45, no. 3, 2012, pp. 495-506 M. Schachter, "The epidemiology of medication errors: how many, how serious?", Br. J. Clin. Pharmacol. 67 (6) (2009) 621–623. T. Morimoto, T.K. Gandhi, A.C. Seger, T.C. Hsieh, D.W. Bates, "Adverse drug events and medication errors: detection and classification methods", Qual. Saf. Health Care 13 (4) (2004) 306–314. K.B. Cohen and L.E. Hunter, "Chapter 16: Text mining for translational bioinformatics", PLOS Computational Biology, P.M. Nadkarni, L. Ohno-Machado, W.W. Chapman, "Natural language processing: an introduction", J Am Med Inform Assoc. 2011 Sep-Oct; 18(5): 544–551. W.W. Chapman et al., "Overcoming barriers to NLP for clinical text – The role of shared tasks and the need for additional creative solutions", J Am Med Inform Assoc. 2011 Sep-Oct;18(5):540-3. I. Spasic, S. Ananiadou, J. McNaught and A. Kumar, "Text mining and ontologies in biomedicine: Making sense of raw text", Brief Bioinform. 2005 Sep;6(3):239-51. A.K. Triantafyllidis, C. Velardo, D. Salvi, S. Ahmar Shah, V.G. Koutkias and L. Tarassenko, "A Survey of Mobile Phone Sensing, Self-reporting and Social Sharing for Pervasive Healthcare", IEEE Journal of Biomedical and Health Informatics, vol 21. no. 1, 2017, pp. 218-227, V. Koutkias, N. Kaklanis, K. Votis, D. Tzovaras and N. Maglaveras, "An Integrated Semantic Framework Supporting Universal Accessibility to ICT", Universal Access in the Information Society, vol. 15, no. 1, 2016, pp. 49-62, A.K. Triantafyllidis, V.G. Koutkias, I. Chouvarda and N. Maglaveras, "A Pervasive Health System Integrating Patient Monitoring, Status Logging and Social Sharing", IEEE Journal of Biomedical and Health Informatics, vol. 17, no. 1, 2013, pp. 30-37, M. Jung, A. Hoerbst, W.O. Hackl, F. Kirrane, D. Borbolla, M.W. Jaspers, M. Oertle, V. Koutkias, L. Ferret, P. Massari, K. Lawton, D. Riedmann, S. Darmoni, N. Maglaveras, C. Lovis and E. Ammenwerth, "Attitude of physicians towards automatic alerting in Computerized Physician Order Entry systems: A comparative international survey", Methods of Information in Medicine, vol. 52, no. 2, 2013, pp. 99-108, V.G. Koutkias, I. Chouvarda and N. Maglaveras, "A Multiagent System Enhancing Home-Care Health Services for Chronic Disease Management", IEEE Transactions on Information Technology in Biomedicine, vol. 9, no. 4, December 2005, pp. 528-537, V.G. Koutkias, I. Chouvarda, A. Triantafyllidis, A. Malousi, G.D. Giaglis, and N. Maglaveras, "A Personalized Framework for Medication Treatment Management in Chronic Care", IEEE Transactions on Information Technology in Biomedicine, vol. 14, no. 2, 2010, pp. 464-472, P. Natsiavas, N. Maglaveras and V. Koutkias, "A Public Health Surveillance Platform Exploiting Free-text Sources via Natural Language Processing and Linked Data: Application in Adverse Drug Reaction Signal Detection using PubMed and Twitter", In: Riaño D., Lenz R., Reichert M. (Eds.), Knowledge Representation for Health Care. KR4HC 2016, ProHealth 2016. Lecture Notes in Computer Science, vol. 10096, pp. 51-67, Springer, 2017. N. Maglaveras, V. Kilintzis, V. Koutkias and I. Chouvarda, "Integrated Care and Connected Health Approaches Leveraging Personalised Health through Big Data Analytics", Studies in Health Technology and Informatics, Vol. 224, pp. 117-122, IOS Press, 2016. J. Bouaud and V. Koutkias, "Computerized Clinical Decision Support: contributions from 2014", Yearb Med Inform. 2015;10:119-124. V. Koutkias and J. Bouaud, “Computerized Clinical Decision Support: contributions from 2015”, Yearb Med Inform. 2016;11:170-177. V. Koutkias and J. Bouaud, “Contributions from the 2016 Literature on Clinical Decision Support”, Yearb Med Inform. 2017;12:133-138. V. Koutkias and J. Bouaud, “Contributions from the 2017 Literature on Clinical Decision Support”, Yearb Med Inform. 2018;13:122-128. V. Koutkias and F. Thiessard, "Big Data - Smart Health Strategies: Findings from the Yearbook 2014 Special Theme", Yearb Med Inform. 2014;9:48-51. doi: 10.15265/IY-2014-0031. K. Vaporidi, D. Babalis, A. Chytas, E. Lilitsis, E. Kondili, V. Amargianitakis, I. Chouvarda, N. Maglaveras and D. Georgopoulos, "Clusters of ineffective efforts during mechanical ventilation: impact on outcome", Intensive Care Med. 2016 Oct 24. DOI: 10.1007/s00134-016-4593-z.
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