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Informatik 5
Information Systems
Prof. Dr. M. Jarke
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Big Data in Medical Informatics

Type Lecture
Term WS 16/17

This module will cover methods for the representation, interpretation and analysis of biomedical data. We will cover data interoperability methods, standards, terminologies for electronic health records and genomic data, as well as predictive analytics and decision making systems in medicine. Algorithmic and methodological approaches will be introduced with practical applications using the R programming language and the Galaxy open source platform. The topics of the lectures are • Biomedical data sources and standards • Biomedical data interoperability • Semantic technologies in biomedicine • Methods and tools for biomedical analysis • Predictive analytics and decision making systems • Genomic data analysis

After completing this module, students should be able to recall and explain

•  Sources and acquisition methods of biomedical data

•  Biomedical data representation and exchange standards

•  Methods for analyzing biomedical data

•  Types of predictive and decision making systems in medicine

•  Challenges in analyzing biomedical data

•  Application of Semantic technologies in the biomedical domain

The students should be able to explain and apply the following techniques:

•  Being able to understand and work with various types of biomedical big data

•  Apply syntactic and semantic data exchange methods

•  Design and apply biomedical data analysis flows

•  Identify predictive algorithms for a given challenge

•  Work with genomic data analytics tools


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