Detailed Information on Publication Record
2023
Data-driven decision-making in medical education and healthcare
KOMENDA, MartinBasic information
Original name
Data-driven decision-making in medical education and healthcare
Name in Czech
Datově orientované rozhodování v lékařském vzdělávání a zdravotní péči
Name (in English)
Data-driven decision-making in medical education and healthcare
Authors
Edition
1. vyd. Brno, 2023
Publisher
koedice Masarykova univerzita / Ústav zdravotnických informací a statistiky ČR
Other information
Language
Czech
Type of outcome
Odborná kniha
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"
ISBN
978-80-280-0392-0
Keywords (in Czech)
datově orientované rozhodování, medicínské vzdělávání, zdravotnické informace, otevřená data
Keywords in English
data-driven decision-making, medical education, health information, open data
Tags
Tags
International impact, Reviewed
Změněno: 18/12/2023 09:25, Mgr. Martina Švaříčková Hlavatá
V originále
At a time when we are surrounded by the everyday use of communication and information technologies very closely linked to the Internet, it is challenging to discern the accuracy, truthfulness and objectivity of the information presented and published. This book and its chapters aim to provide an overview of selected projects and activities across the academic and governmental domains focused on data processing and visualisation. It is crucial to recognise that, given the volume of data of varying quality that we now have at our disposal, we need to focus much more on understanding, identifying, and distributing correct information and inferences directly from the data. This is the main reason why this book was written. The individual case studies focus on examples of both good and bad practices, drawing on experiences from real-life projects. Data should always serve as a basis for decision-making processes and mechanisms, but only if they are correctly processed, understood, and, above all, interpreted. There are various ways to present results over descriptive statistics and data analysis, from summary tables to static graphs, to interactive web visualisations. It is only possible to say which type and presentation format is best with additional information (such as the target audience or primary purpose of use). The selected chapters in this book highlight the complete lifecycle of understanding, processing, visualising and validating data, so that all of the critical components of this process are remembered.
In English
At a time when we are surrounded by the everyday use of communication and information technologies very closely linked to the Internet, it is challenging to discern the accuracy, truthfulness and objectivity of the information presented and published. This book and its chapters aim to provide an overview of selected projects and activities across the academic and governmental domains focused on data processing and visualisation. It is crucial to recognise that, given the volume of data of varying quality that we now have at our disposal, we need to focus much more on understanding, identifying, and distributing correct information and inferences directly from the data. This is the main reason why this book was written. The individual case studies focus on examples of both good and bad practices, drawing on experiences from real-life projects. Data should always serve as a basis for decision-making processes and mechanisms, but only if they are correctly processed, understood, and, above all, interpreted. There are various ways to present results over descriptive statistics and data analysis, from summary tables to static graphs, to interactive web visualisations. It is only possible to say which type and presentation format is best with additional information (such as the target audience or primary purpose of use). The selected chapters in this book highlight the complete lifecycle of understanding, processing, visualising and validating data, so that all of the critical components of this process are remembered.