Informações sobre o curso
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100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 23 horas para completar

Sugerido: 5 weeks of study, 2-4 hours/week...

Inglês

Legendas: Inglês

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 23 horas para completar

Sugerido: 5 weeks of study, 2-4 hours/week...

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
4 horas para concluir

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. ...
9 vídeos (total de (Total 54 mín.) min), 4 leituras, 1 teste
9 videos
Clinical Research Data Warehouses9min
Entity Relationship Diagrams (ERDs)4min
Clinical Data Models4min
Why Common Data Models?10min
A Quick Tour of a Common Data Model: i2b26min
A Quick Tour of a Common Data Model: OMOP5min
A Quick Tour of a Common Data Model: Sentinel6min
A Quick Tour of a Common Data Model: PCORNet5min
4 leituras
Introduction to Specialization Instructors5min
Course Policies5min
Accessing Course Data and Technology Platform15min
Readings and Course Materials for Module 1s
1 exercício prático
Clinical Data Models and Common Data Models30min
Semana
2
3 horas para concluir

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....
6 vídeos (total de (Total 59 mín.) min), 1 leitura, 1 teste
6 videos
Querying MIMIC-III9min
A Deep Dive into OMOP Data Model13min
Querying OMOP12min
Comparing the MIMIC and OMOP Data Models10min
The OHDSI Community Ecosystem7min
1 leituras
Readings and Course Materials for Module 230min
1 exercício prático
Tools: Querying Clinical Data Models30min
Semana
3
3 horas para concluir

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. ...
6 vídeos (total de (Total 53 mín.) min), 1 leitura, 1 teste
6 videos
Structural versus Terminology Mapping6min
Data Profiling with White Rabbit10min
Data Mapping with the Rabbit in a Hat Tool9min
Terminology Mapping10min
Example mapping of MIMIC Patient to OMOP Person8min
1 leituras
Readings and Course Materials for Module 3s
1 exercício prático
Techniques: Extract-Transform-Load and Terminology Mapping30min
Semana
4
3 horas para concluir

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....
5 vídeos (total de (Total 52 mín.) min), 1 leitura, 1 teste
5 videos
Data profiling for data quality assessment10min
Data quality assessment using SQL13min
Callahan and Khare rules8min
OHDSI Achilles and Achilles Heel12min
1 leituras
Readings and Course Materials for Module 430min
1 exercício prático
Techniques: Data Quality Assessments30min

Instrutores

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Laura K. Wiley, PhD

Assistant Professor
Division of Biomedical Informatics and Personalized Medicine, Anschutz Medical Campus
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Michael G. Kahn, MD, PhD

Professor of Clinical Informatics
Department of Pediatrics, Anschutz Medical Campus

Sobre Sistema de Universidades do ColoradoUniversidade do Colorado

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....

Sobre o Programa de cursos integrados 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! This specialization provides learners with hands on experience in use of electronic health records and informatics tools to perform clinical data science. This series of six courses is designed to augment learner’s existing skills in statistics and programming to provide examples of specific challenges, tools, and appropriate interpretations of clinical data. By completing this specialization you will know how to: 1) understand electronic health record data types and structures, 2) deploy basic informatics methodologies on clinical data, 3) provide appropriate clinical and scientific interpretation of applied analyses, and 4) anticipate barriers in implementing informatics tools into complex clinical settings. You will demonstrate your mastery of these skills by completing practical application projects using real clinical data. This specialization is supported by our industry partnership with Google Cloud. Thanks to this support, all learners will have access to a fully hosted online data science computational environment for free! Please note that you must have access to a Google account (i.e., gmail account) to access the clinical data and computational environment....
Clinical Data Science

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

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