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

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Další údaje

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"

Odkazy

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

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Anotace

V originále

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.

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.