title: Future perspectives toward the early definition of a multivariate decision-support scheme employed in clinical decision making for senior citizens.
abstract: Recent neuroscientific studies focused on the identification of pathological neurophysiological patterns (emotions, geriatric depression, memory impairment and sleep disturbances) through computerised clinical decision-support systems. Almost all these research attempts employed either resting-state condition (e.g. eyes-closed) or event-related potentials extracted during a cognitive task known to be affected by the disease under consideration. This Letter reviews existing data mining techniques and aims to enhance their robustness by proposing a holistic decision framework dealing with comorbidities and early symptoms' identification, while it could be applied in realistic occasions. Multivariate features are elicited and fused in order to be compared with average activities characteristic of each neuropathology group. A proposed model of the specific cognitive function which may be based on previous findings (a priori information) and/or validated by current experimental data should be then formed. So, the proposed scheme facilitates the early identification and prevention of neurodegenerative phenomena. Neurophysiological semantic annotation is hypothesised to enhance the importance of the proposed framework in facilitating the personalised healthcare of the information society and medical informatics research community.
authors.affiliation: Laboratory of Medical Physics, Medical School, Faculty of Health Sciences , Aristotle University of Thessaloniki , Thessaloniki , Greece.
authors.forename: Christos A
authors.initials: CA
authors.lastname: Frantzidis
authors.affiliation: Laboratory of Medical Physics, Medical School, Faculty of Health Sciences , Aristotle University of Thessaloniki , Thessaloniki , Greece.
authors.forename: Sotiria
authors.initials: S
authors.lastname: Gilou
authors.affiliation: Laboratory of Medical Physics, Medical School, Faculty of Health Sciences , Aristotle University of Thessaloniki , Thessaloniki , Greece.
authors.forename: Antonis
authors.initials: A
authors.lastname: Billis
authors.affiliation: Laboratory of Medical Physics, Medical School, Faculty of Health Sciences , Aristotle University of Thessaloniki , Thessaloniki , Greece.
authors.forename: Maria
authors.initials: M
authors.lastname: Karagianni
authors.affiliation: Department of Mathematics , Aristotle University of Thessaloniki , Thessaloniki , Greece.
authors.forename: Charalampos D
authors.initials: CD
authors.lastname: Bratsas
authors.affiliation: Laboratory of Medical Physics, Medical School, Faculty of Health Sciences , Aristotle University of Thessaloniki , Thessaloniki , Greece.
authors.forename: Panagiotis
authors.identifier: 0000-0002-9936-5805
authors.initials: P
authors.lastname: Bamidis
keywords: clinical decision making; data mining; data mining techniques; decision making; decision support systems; electroencephalography; geriatrics; holistic decision framework; medical signal processing; multivariate decision-support scheme; neurodegenerative phenomena; neurophysiological semantic annotation; neurophysiology; pathological neurophysiological patterns; senior citizens