880005 :Health Analytics (CSAI/HAIT)

Algemeen

Voertaal Engels
Werkvorm: Lectures and hands-on sessions (Collegerooster)
Tentamenvorm: Written exam, 2 papers (Tentamenrooster)
Niveau:Master
Studielast:6 ECTS credits
Inschrijving:Enrollment via Blackboard before start of lectures
Blackboard informatieLink to Blackboard (Als u de melding 'Guest are not allowed in this course' krijgt, dient u nog bij Blackboard in te loggen)

Docent(en)


dr. W. Huijbers (coördinator)


Doel van de cursus (alleen in het Engels beschikbaar)

Health analytics is a rapidly growing domain of data science. In this course, we will focus on key concepts in public health and epidemiology. We will discuss applications of these concepts in research, policy making in health care. For example, how data collection is limited by observational biases that influence analysis results. Understanding of epidemiological concepts is crucial for the interpretation of results from large amounts of health data. The course will put emphasis on theory, ideas, and epidemiological axioms. Theory will be combined with hands-on exercises in data visualization and basic data mining experiments. During the course, practitioners working in the field of health analytics will be invited to discuss applications in different medical contexts.


Inhoud van de cursus (alleen in het Engels beschikbaar)

Health analytics is a rapidly growing domain of data science. In this course, we will focus on key concepts in public health and epidemiology. We will discuss applications of these concepts in research, policy making in health care. For example, how data collection is limited by observational biases that influence analysis results. Understanding of epidemiological concepts is crucial for the interpretation of results from large amounts of health data. The course will put emphasis on theory, ideas, and epidemiological axioms. Theory will be combined with hands-on exercises in data visualization and basic data mining experiments. During the course, practitioners working in the field of health analytics will be invited to discuss applications in different medical contexts.


Bijzonderheden (alleen in het Engels beschikbaar)

Some basic understanding of biology is helpful, as is some familiarity with illness and disease, but a medical background in not necessary. The exercises and assignments will consist of simple programming in R and Python. No prior knowledge is required, but without any programming experience, some additional work will be required, in order to keep up.


Verplichte literatuur

  1. Bhopal RS., Concepts of Epidemiology, Oxford University Press (can be found online), 2002. and scientific articles announced on Blackboard


Vereiste voorkennis

880254 RS:Data Processing or 880256 RS:Programming with R


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  • Communication and Information Sciences ( 2017 )
  • Cognitive Science and Artificial Intelligence ( 2017 )

(18-jul-2017)