This course aims to teach the concepts of clinical data models and common data models. Upon completion of this course, learners will be able to interpret and evaluate data model designs using Entity-Relationship Diagrams (ERDs), differentiate between data models and articulate how each are used to support clinical care and data science, and create SQL statements in Google BigQuery to query the MIMIC3 clinical data model and the OMOP common data model.
Ce cours fait partie de la Spécialisation Clinical Data Science
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Spécialisation Clinical Data ScienceUniversity of Colorado SystemÀ propos de ce cours
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Cours 2 sur 6 dans le
Niveau intermédiaire
Approx. 17 heures pour terminer
Anglais
Sous-titres : Anglais
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 2 sur 6 dans le
Niveau intermédiaire
Approx. 17 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
University of Colorado System
The University of Colorado is a recognized leader in higher education on the national and global stage. We collaborate to meet the diverse needs of our students and communities. We promote innovation, encourage discovery and support the extension of knowledge in ways unique to the state of Colorado and beyond.
Programme de cours : ce que vous apprendrez dans ce cours
4 heures pour terminer
Introduction: Clinical Data Models and Common Data Models
This week describes clinical data models and explains the need for and use of common data models in national and international data networks. We will also cover the features of Entity-Relationship Diagrams (ERDs) to describe the key technical features of data models.
4 heures pour terminer
9 vidéos (Total 54 min), 4 lectures, 1 quiz
3 heures pour terminer
Tools: Querying Clinical Data Models
We take a deep dive into the technical features of clinical data models using MIMIC3 as our example and research common data models using OMOP as our example.
3 heures pour terminer
6 vidéos (Total 59 min), 1 lecture, 1 quiz
3 heures pour terminer
Techniques: Extract-Transform-Load and Terminology Mapping
This module teaches learners about the processes and challenges with extracting, transforming and loading (ETL) data with real-world examples in data and terminology mapping.
3 heures pour terminer
6 vidéos (Total 53 min), 1 lecture, 1 quiz
3 heures pour terminer
Techniques: Data Quality Assessments
We explore the dimensions of data quality by reviewing its challenges, data quality measurements used to measure it, and data quality rules to assess its acceptability for use.
3 heures pour terminer
5 vidéos (Total 52 min), 1 lecture, 1 quiz
Avis
- 5 stars50 %
- 4 stars29,62 %
- 3 stars12,96 %
- 2 stars3,70 %
- 1 star3,70 %
Meilleurs avis pour CLINICAL DATA MODELS AND DATA QUALITY ASSESSMENTS
par FG12 déc. 2019
An excellent course that provides great guidelines for clinical data models. There are plenty of exercises to cement each block of learning material.
par VT13 sept. 2019
Good instructor who took time to explain and walked through each steps of the ETL process. Highly recommended.
par MK21 juil. 2019
Gives a great understanding of ETL and the surrounding concepts from Zero. I personally found that a little boring, but for a total newbie to data and computers this is a perfect course.
par MK4 nov. 2019
What a great course!! Kudos to the professor for being so detail oriented!! I learned a great deal about the clinical data models from this course!!
À propos du Spécialisation Clinical Data Science
Are you interested in how to use data generated by doctors, nurses, and the healthcare system to improve the care of future patients? If so, you may be a future clinical data scientist!
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