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https://hdl.handle.net/123456789/1669| Τύπος: | Ανακοίνωση σε συνέδριο |
| Τίτλος: | Use of volatile organic compounds for the identification of high risk patients with Chronic Obstructive Pulmonary Disease |
| Συγγραφέας: | [EL] Έξαρχος, Κωνσταντίνος[EN] Exarchos, Konstantinos [EL] Κωστίκας, Κωνσταντίνος[EN] Kostikas, Konstantinos [EL] Σακκάς, Βασίλειος[EN] Sakkas, Vasileios [EL] Χρόνης, Χρήστος[EN] Chronis, Christos |
| Ημερομηνία: | Οκτ-2020 |
| Περίληψη: | Chronic Obstructive Pulmonary Disease (COPD) is currently the fourth leading cause of death in the world, posing a major health challenge that is currently considered as preventable and treatable. During the course of the disease, periods of acute worsening of respiratory symptoms called exacerbations, account for the greatest proportion of COPD burden, both in terms of quality of life and healthcare costs. To this end, several biomarkers have been proposed in the literature aiming to identify those patient subgroups that have a higher risk for exacerbations, yet their utilization in clinical practice remains minimal. In this work, we employ Volatile Organic Compounds (VOCs) analysis, whereby VOCs are identified in COPD patients’ breath and quantified via gas chromatography coupled with mass spectrometry. VOCs capture underlying metabolic processes, and constitute a non-invasive biomarker that has been used in several health applications with promising results. In the present study we have enrolled 27 patients diagnosed with COPD, and each patient has been assigned either as high or low risk, based on a combined index of their exacerbation history and blood eosinophil counts. The median age of enrolled patients is 70 with a standard deviation of 6.8 years. The VOCs’ compositions comprise the feature vector that is subsequently fed to a series of classification algorithms, namely Bayes Network, Naive Bayes, Decision Trees, Artificial Neural Networks, Support Vector Machines, Random Forests and AdaBoostM1 in order to discern the two classes of patients. Prior to the classification task we also employ certain feature selection techniques aiming to pinpoint the most informative VOCs. |
| Γλώσσα: | Αγγλικά |
| Τόπος δημοσίευσης: | Virtually |
| Σελίδες: | 1 |
| Θεματική κατηγορία: | [EL] Πνευμονολογία και Αναπνευστικές παθήσεις[EN] Pulmonary and Respiratory Medicine |
| Κάτοχος πνευματικών δικαιωμάτων: | © The Author(s) 2021 |
| Όνομα εκδήλωσης: | 4th World Congress on Genetics, Geriatrics and Neurodegenerative Disease Research (GeNeDis) |
| Τοποθεσία εκδήλωσης: | Virtual Conference |
| Ημ/νία έναρξης εκδήλωσης: | 08/10/2020 |
| Ημ/νία λήξης εκδήλωσης: | 11/10/2020 |
| Εμφανίζεται στις συλλογές: | Ερευνητικές ομάδες |
Αρχεία σε αυτό το τεκμήριο:
| Αρχείο | Περιγραφή | Σελίδες | Μέγεθος | Μορφότυπος | Έκδοση | Άδεια | |
|---|---|---|---|---|---|---|---|
| B47.pdf Restricted Access | Use of Volatile Organic Compounds for the identification of high risk patients with Chronic Obstructive Pulmonary Disease | 136.08 kB | Adobe PDF | - |  | Δείτε/ανοίξτε |