inf529 - Big Data in Medicine (Complete module description)

Module label	Big Data in Medicine
Modulkürzel	inf529
Credit points	6.0 KP
Workload	180 h
Institute directory	Department of Computing Science
Verwendbarkeit des Moduls	Bachelor's Programme Business Informatics (Bachelor) > Akzentsetzungsbereich Praktische Informatik und Angewandte Informatik Bachelor's Programme Computing Science (Bachelor) > Akzentsetzungsbereich - Wahlbereich Informatik Master of Education Programme (Hauptschule and Realschule) Computing Science (Master of Education) > Mastermodule
Zuständige Personen	Wulff, Antje (module responsibility) Lehrenden, Die im Modul (Prüfungsberechtigt)
Prerequisites	No specific prior knowledge is required
Skills to be acquired in this module	Introduction to the subfield "Big Data in Medicine" from the field of medical informatics. Professional competences The students know the definition and meaning of "Big Data" in the medical context know the challenges of dealing with healthcare data sets know the Big Data pipeline, technologies and examples from the different areas of the pipeline for the medical context Methological competences The students recognize potentials and challenges in data-driven use cases from the healthcare sector can describe the characteristics of medical data sets using the methods learned can design solutions for medical, data-driven issues using the methods learned Social competences The students recognize the importance of interdisciplinary communication and collaboration in the analysis of medical data develop, present and discuss the solutions from the exercises with others Self competences The students know their responsibilities when dealing with medical records reflect on problems and solutions, incorporating the methods they have learned
Module contents	The assigned lectures will provide an overview of the subject area "Big Data in Medicine" and the particular challenges and characteristics of medical data and its sources, (storage) technologies, and processing and presentation options.
Literaturempfehlungen	Ralf Otte, Boris Wippermann, Sebastian Schade, Viktor Otte – Von Data Mining bis Big Data, Handbuch für die industrielle Praxis. HANSER, ISBN: 9783446455504 Detlev Frick, Andreas Gadatsch, Jens Kaufmann, Birgit Lankes, Christoph Quix, Andreas Schmidt, Uwe Schmitz (Hrsg.) – Data Science, Konzepte, Erfahrungen, Fallstudien und Praxis. Springer Vieweg, 978-3658334024 Holm Landrock, Andreas Gadatsch – Big Data im Gesundheitswesen kompakt, Konzepte, Lösungen, Visionen. Springer Vieweg, 978-3-658-21096-0 Further will be announced in the course
Links
Languages of instruction	German, English
Duration (semesters)	1 Semester
Module frequency	every summer term
Module capacity	unlimited
Teaching/Learning method	V+Ü oder PR

Form of instruction	SWS	Frequency	Workload of compulsory attendance
Lecture	2	SoSe	28
Exercise or project	2	SoSe	28
Präsenzzeit Modul insgesamt			56 h

Examination	Prüfungszeiten	Type of examination
Final exam of module	at the end of the lecture period	Written or oral exam The chosen form of examination will be announced in the first week of the course