NBE-E4080 - Decision Support in Healthcare D, Lecture, 23.10.2023-29.12.2023

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Upon successful completion of this course, the student:

  • Understands and can independently formulate data-analysis requirements associated with different healthcare decision making tasks (risk assessment, early diagnosis, differential diagnosis, treatment planning, and treatment follow-up)
  • Can recognize what kind of approaches (data-driven, rule-based, mechanistic models etc) are most appropriate for what decision-making challenge
  • Has knowledge of, and knows how to select and apply methods for data curation and quality assurance
  • Has an understanding of the most common feature extraction and feature selection methods
  • Has gained knowledge of the most common AI/ML methods for advanced decision support
  • Understands how to objectively assess the performance of AI/ML methods in common healthcare decision support settings
  • Understands considerations such as explainability, privacy-preservation, bias and ethics in computer-based decision support in health and know which tools are available to address these.

Credits: 5

Schedule: 23.10.2023 - 29.12.2023

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Marcus van Gils

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    See Learning outcomes

Assessment Methods and Criteria

  • valid for whole curriculum period:

    exercises, exam

Workload

  • valid for whole curriculum period:

    lectures, exercises

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Autumn II
    2023-2024 Autumn II

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