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In: Fundamentals of Clinical Data Science [Internet]. Cham (CH): Springer; 2019. Chapter 2.
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Affiliations
Affiliations
1 Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
2 Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
3 Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Center, Maastricht, The Netherlands
Book Affiliations
1 Department of Neurosurgery, Maastricht University, Maastricht, Limburg, The Netherlands
2 Institute of Data Science, Maastricht University, Maastricht, Limburg, The Netherlands
3 Maastro Clinic, Maastricht, Limburg, The Netherlands
1 Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
2 Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
3 Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Center, Maastricht, The Netherlands
Book Affiliations
1 Department of Neurosurgery, Maastricht University, Maastricht, Limburg, The Netherlands
2 Institute of Data Science, Maastricht University, Maastricht, Limburg, The Netherlands
3 Maastro Clinic, Maastricht, Limburg, The Netherlands
Pre-requisites to better understand the chapter: basic knowledge of major sources of clinical data.
Logical position of the chapter with respect to the previous chapter: in the previous chapter, you have learned what the major sources of clinical data are. In this chapter, we will dive into the main characteristics of presented data sources. In particular, we will learn how to distinguish and classify data according to its scale.
Learning objectives: you will learn the major differences between data sources presented in previous chapters; how clinical data can be classified according to its scale. You will get familiar with the concept of ‘big’ clinical data; you will learn which are the major concerns limiting ‘big’ data exchange.
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