inf527 - Big Data Analytics and Clinical Decision Support

inf527 - Big Data Analytics and Clinical Decision Support

Department of Computing Science 6 KP
Module components Semester courses Winter semester 2024/2025 Examination
Lecture
Exercise or project
Notes on the module
Prerequisites

No specific prior knowledge is required
Prüfungszeiten

at the end of the lecture period
Module examination

Portfolio, written exam, practical exercise or oral exam

The chosen form of examination will be announced in the first week of the course
Skills to be acquired in this module

In-depth understanding about the processing of medical data sets in the context of Data Analytics, Big Data in medicine and the development and importance of (decision) support tools.

Professional competences

The students

  • know the sources, characteristics and diversity of medical data and the significance of Big Data in medicine
  • know methods for designing (decision) support applications, including the processing of relevant data and information, with regard to a medical issue
  • know application classes and types of (decision) support applications and tools
  • know professional, organizational and regulatory requirements and framework conditions for data analysis and application development in the healthcare sector

Methological competences
The students  

  • can familiarize themselves with a medical, data-driven problem and solve it using familiar methods from the various areas of requirements elicitation, knowledge management, conception, implementation and evaluation
  • can process given data in a targeted manner with regard to a medical- informational problem and discuss results critically
  • can present and hand over results, e.g. decision support applications (especially for medical experts), in a way that adds value.

Social competences
The students

  • learn the interdisciplinary exchange in this context and understand its importance and necessity
  • develop, present and discuss the solutions from the exercises with others

Self competences
The students

  • can assess their role and importance in the analysis of medical data and the development of medical support applications/tools
  • recognize the limits of their (specialist) perspective and the added value of the domain knowledge of others
  • critically reflect on problems and solutions, incorporating the methods they have learned

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