ANTOL, Matej, Michal RŮŽIČKA, Luděk MATYSKA and Jiří MAREK. Public (Health) Sector and Academia. In Martin Komenda. 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.
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Basic information
Original name Public (Health) Sector and Academia
Name (in English) Public (Health) Sector and Academia
Authors ANTOL, Matej (703 Slovakia, guarantor, belonging to the institution), Michal RŮŽIČKA (203 Czech Republic, belonging to the institution), Luděk MATYSKA (203 Czech Republic, belonging to the institution) and Jiří MAREK (203 Czech Republic, belonging to the institution).
Edition First edition. Brno, Data-Driven Decision-Making in Medical Education and Healthcare, p. 51-66, 16 pp. Data Rulezzzz! 2023.
Publisher Masaryk University
Other information
Original language Czech
Type of outcome Chapter(s) of a specialized book
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
WWW Book home page
RIV identification code RIV/00216224:14610/23:00132315
Organization unit Institute of Computer Science
ISBN 978-80-280-0392-0
Keywords in English Open Science; EOSC; Data Management; DMP
Tags International impact, Reviewed
Changed by Changed by: RNDr. Michal Růžička, Ph.D., učo 143424. Changed: 20/11/2023 14:58.
Abstract
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.
Abstract (in English)
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.
PrintDisplayed: 19/7/2024 14:11