Learning Outcomes
By the end of this course students will be able to:
-understand the basic concepts of computer science and the basic software tools that are relevant to the subject of pharmacology
-realize the importance of managing information through software systems and decision support systems and be able to implement them in practice
-adopt new technologies in their lifelong learning
-be aware of the latest software tools in the field of pharmaceutical research and practice (desktop and mobile)
-be aware of the importance of specific research topics related to pharmacology and the search for data and bibliographic sources
-use advanced statistical methodologies for pharmaceutical research
-apply multifactorial analysis, completeness check of the assumptions of each multifactor model, and choice of final model
Course Content (Syllabus)
Health Informatics - Introduction, modern concepts, applications and tools
Open and interconnected data. Big data: Principles of learning and extracting knowledge about adverse drug reactions
Online pharmacology databases. DrugBank: Search and export of information using open interconnected data techniques.
Research surveys - organization and implementation workshop
Tools and technologies for organizing research and writing the bibliography
Multi-factorial linear dependence
Multifactorial regression and dependence
Multi-factorial risk Cox model
Keywords
Health Informatics, social media, semantic web, big data, research survey, organsing research
Additional bibliography for study
-Π. Μπαμίδης, Κ. Παπάς, Ιατρική Πληροφορική & Διαδίκτυο στις Σύγχρονες Υπηρεσίες Υγείας, (Έκδοση) Υγειονομική Περιφέρεια Μακεδονίας, Θεσσαλονίκη, 2008
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