Other formats:
BibTeX
LaTeX
RIS
@inbook{2341268, author = {Antol, Matej and Růžička, Michal and Matyska, Luděk and Marek, Jiří}, address = {Brno}, booktitle = {Data-Driven Decision-Making in Medical Education and Healthcare}, edition = {First edition}, editor = {Martin Komenda}, keywords = {Open Science; EOSC; Data Management; DMP}, howpublished = {tištěná verze "print"}, language = {cze}, location = {Brno}, isbn = {978-80-280-0392-0}, pages = {51-66}, publisher = {Masaryk University}, title = {Public (Health) Sector and Academia}, url = {https://iba.med.muni.cz/en/data-rulezzz}, year = {2023} }
TY - CHAP ID - 2341268 AU - Antol, Matej - Růžička, Michal - Matyska, Luděk - Marek, Jiří PY - 2023 TI - Public (Health) Sector and Academia VL - Data Rulezzzz! PB - Masaryk University CY - Brno SN - 9788028003920 KW - Open Science KW - EOSC KW - Data Management KW - DMP UR - https://iba.med.muni.cz/en/data-rulezzz N2 - This book is divided into three main sections: 1. The big picture (general background and methodologies) 2. Medical and healthcare education in selected case studies 3. Health information and statistics in selected case studies Each chapter, except the big picture, has the same format describing a particular project result as a case study, which is always based on a well-proven interdisciplinary methodology (specifically CRISP-DM – Cross-Industry Process for Data Mining – the structured approach to planning and running data mining projects. – As a methodology, it includes descriptions of individual project phases, the tasks involved with each stage, and the relationships between them. – As a process model, it provides an overview of the complete data mining life cycle. ER -
ANTOL, Matej, Michal RŮŽIČKA, Luděk MATYSKA and Jiří MAREK. Public (Health) Sector and Academia. In Martin Komenda. \textit{Data-Driven Decision-Making in Medical Education and Healthcare}. First edition. Brno: Masaryk University, 2023, p.~51-66. Data Rulezzzz! ISBN~978-80-280-0392-0.
|