inf529 - Big Data in Medicine (Complete module description)

inf529 - Big Data in Medicine (Complete module description)

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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 1VL + 1Ü oder 1PR
Previous knowledge none
Form of instruction Comment 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