Public (Health) Sector and Academia

ANTOL, Matej, Michal RŮŽIČKA, Luděk MATYSKA a 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, s. 51-66. Data Rulezzzz! ISBN 978-80-280-0392-0.

Základní údaje

• Originální název: Public (Health) Sector and Academia
• Název anglicky: Public (Health) Sector and Academia
• Autoři: ANTOL, Matej (703 Slovensko, garant, domácí), Michal RŮŽIČKA (203 Česká republika, domácí), Luděk MATYSKA (203 Česká republika, domácí) a Jiří MAREK (203 Česká republika, domácí).
• Vydání: First edition. Brno, Data-Driven Decision-Making in Medical Education and Healthcare, od s. 51-66, 16 s. Data Rulezzzz! 2023.
• Nakladatel: Masaryk University

Další údaje

• Originální jazyk: čeština
• Typ výsledku: Kapitola resp. kapitoly v odborné knize
• Obor: 10201 Computer sciences, information science, bioinformatics
• Stát vydavatele: Česká republika
• Utajení: není předmětem státního či obchodního tajemství
• Forma vydání: tištěná verze "print"
• WWW: Book home page
• Kód RIV: RIV/00216224:14610/23:00132315
• Organizační jednotka: Ústav výpočetní techniky
• ISBN: 978-80-280-0392-0
• Klíčová slova anglicky: Open Science; EOSC; Data Management; DMP
• Příznaky: Mezinárodní význam, Recenzováno

Anotace

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.

Anotace anglicky

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.