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Avis et commentaires pour d'étudiants pour Foundations of mining non-structured medical data par EIT Digital

21 évaluations

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The goal of this course is to understand the foundations of Big Data and the data that is being generated in the health domain and how the use of technology would help to integrate and exploit all those data to extract meaningful information that can be later used in different sectors of the health domain from physicians to management, from patients to caregivers, etc. The course offers a high-level perspective of the importance of the medical context within the European context, the types of data that are managed in the health (clinical) context, the challenges to be addressed in the mining of unstructured medical data (text and image) as well as the opportunities from the analytical point of view with an introduction to the basics of data analytics field....

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1 - 9 sur 9 Avis pour Foundations of mining non-structured medical data

par David L H

31 janv. 2019

Fascinating information- really improved my knowledge of the tools that are available in the clinical data space.

par Dinesh K R

23 juin 2021

Good Content. Thanks

par m v

15 juil. 2020

Thank you professors

par Jenny

11 nov. 2019

great introduction to data mining. I have been looking for a course that does not require too much background for quite some time and this one was just the right degree of complexity. I now feel confident that I have a solid foundation to build on.

par Prachiti P

28 avr. 2020

Contents very well covered.but I found answer of 2-3 question of quiz was wrong even though it was correct.I have added that questions in discussion forum as well. Otherwise it was happy learning with all instructors.thank you for this course.

par Manish

4 janv. 2019

Good course of initial and high level understanding of basic concepts


18 mai 2020

Provided an introduction to datamining

par Novi A

9 nov. 2019

Language barrier.

par Fakir M P

2 déc. 2021

before starting this course , learn basics of machine learning alogorithms and data pre-pocessing basics