Module CS3350-KP06

Duration

1 Semester

Turnus of offer

each winter semester

Credit points

6

Course of studies, specific fields and terms:

• Bachelor Medical Informatics 2014, optional subject, medical computer science
• Bachelor Medical Informatics 2019, compulsory, Medical Data Science / Artificial Intelligence

Classes and lectures:

• Medical Data Science and Artificial Intelligence (exercise, 2 SWS)
• Medical Data Science and Artificial Intelligence (practical course, 1 SWS)
• Medical Data Science and Artificial Intelligence (lecture, 2 SWS)

Workload:

• 40 hours exam preparation
• 65 hours private studies
• 75 hours in-classroom work

Contents of teaching:

• Introduction
• General Approach to Information Retrieval (Scenario 1: Medical Information Retrieval)
• Annotation-based Approach to Information Retrieval (Scenario 1: Medical Information Retrieval)
• Content-based Approach to Information Retrieval (Scenario 1: Medical Information Retrieval)
• Performance of Systems for Information Retrieval (Scenario 1: Medical Information Retrieval)
• General Approach to Supervised Classification (Scenario 2: Intraoperative Patient Monitoring)
• Extraction, Selection and Transformation of Features (Scenario 2: Intraoperative Patient Monitoring)
• Linear Classification (Scenario 2: Intraoperative Patient Monitoring)
• Statistical Classification (Scenario 2: Intraoperative Patient Monitoring)
• General Approach to Unsupervised Classification (Scenario 3: Population Medicine)
• Sequential Clustering (Scenario 3: Population Medicine)
• Hierarchical Clustering (Scenario 3: Population Medicine)
• Fuzzy Clustering (Scenario 3: Population Medicine)
• Demonstrators from Current Research Projects
• Summary and Conclusions

Qualification-goals/Competencies:

• Students know the term Medical Data Science and are able to define and clearly distinguish it from other related terms.
• Students know the concept of the automated information retrieval.
• Students know the annotation-based approach to information retrieval and are able to implement it in the medical context using a programming language.
• Students know the content-based approach to information retrieval and are able to implement it in the medical context using a programming language.
• Students know evaluation strategies for information retrieval platforms and are able to assess the performance of such systems.
• Students know the concept of supervised classification.
• Students know selected approaches to feature extraction, selection, and transformation and are able to implement it in the medical context using a programming language.
• Students know the linear classification approach and are able to implement it in the medical context using a programming language.
• Students know the statistical classification approach and are able to implement it in the medical context using a programming language.
• Students know the concept of unsupervised learning (clustering).
• Students know the sequential clustering approach and are able to implement it in the medical context using a programming language.
• Students know the hierarchical clustering approach and are able to implement it in the medical context using a programming language.
• Students know the fuzzy clustering approach and are able to implement it in the medical context using a programming language.
• Students know the objectives and function of software systems from selected current medical data science research projects.
• Students know the societal relevance of methods for automated data analysis in the medicine.

Grading through:

• Written or oral exam as announced by the examiner

Responsible for this module:

• Prof. Dr.-Ing. Marcin Grzegorzek

Teacher:

• Institute of Medical Informatics
• Prof. Dr.-Ing. Marcin Grzegorzek

Literature:

• Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze : Introduction to Information Retrieval ISBN: 9780521865715
• Sergios Theodoridis and Konstantinos Koutroumbas : Pattern Recognition ISBN: 9781597492720

Language:

• German and English skills required

Notes:

Last Updated:

29.09.2025