C 2023

Public (Health) Sector and Academia

ANTOL, Matej, Michal RŮŽIČKA, Luděk MATYSKA and Jiří MAREK

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

Language

Czech

Type of outcome

Kapitola resp. kapitoly v odborné knize

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

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
Změněno: 20/11/2023 14:58, RNDr. Michal Růžička, Ph.D.

Abstract

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.

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.