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

Some programming experience in any language.

Aprox. 18 horas para completar

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

Inglês

Legendas: Inglês
User
Os alunos fazendo este Course são
  • Scientists
  • Data Scientists
  • Researchers
  • Medical Doctors
  • Data Analysts

O que você vai aprender

  • Check

    Create a computational phenotyping algorithm

  • Check

    Assess algorithm performance in the context of analytic goal.

  • Check

    Create combinations of at least three data types using boolean logic

  • Check

    Explain the impact of individual data type performance on computational phenotyping.

User
Os alunos fazendo este Course são
  • Scientists
  • Data Scientists
  • Researchers
  • Medical Doctors
  • Data Analysts

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Some programming experience in any language.

Aprox. 18 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
2 horas para concluir

Introduction: Identifying Patient Populations

5 vídeos (Total 23 mín.), 9 leituras, 2 testes
5 videos
Introduction to Computational Phenotyping5min
Introduction to Manual Record Review4min
Manual Record Review: Selecting Reviewers and Records6min
Manual Record Review: Tools and Techniques5min
9 leituras
Introduction to Specialization Instructors5min
Course Policies5min
Accessing Course Data and Technology Platform15min
Introduction to Course Example15min
Introduction to Manual Record Review10min
Methods - Selecting Reviewers10min
Methods - Selecting Records for Review10min
Methods - Creating Review Instruments and Protocols10min
Methods - Assessing Review Quality10min
2 exercícios práticos
Week 1 Practice Quiz8min
Week 1 Assessment16min
Semana
2
3 horas para concluir

Tools: Clinical Data Types

5 vídeos (Total 19 mín.), 2 leituras, 2 testes
5 videos
Computational Phenotyping: Billing Data5min
Computational Phenotyping: Laboratory Data3min
Computational Phenotyping: Clinical Observations2min
Computational Phenotyping: Medications3min
2 leituras
Testing Individual Data Types1h 30min
Note about the Assessment2min
2 exercícios práticos
Programming Exercises Practice Quiz30min
Week 2 Assessment18min
Semana
3
3 horas para concluir

Techniques: Data Manipulations and Combinations

2 vídeos (Total 15 mín.), 2 leituras, 2 testes
2 videos
Combining Multiple Data Types5min
2 leituras
Data Manipulations1h 30min
Data Combinations45min
2 exercícios práticos
Programming Exercises Practice Quiz30min
Week 3 Assessment25min
Semana
4
1 hora para concluir

Techniques: Algorithm Selection and Portability

1 vídeo (Total 4 mín.), 1 leitura, 1 teste
1 vídeos
1 leituras
Assessing Algorithmic Accuracy, Complexity, and Portability25min
1 exercício prático
Week 4 Assessment20min
4.5
6 avaliaçõesChevron Right

Principais avaliações do Identifying Patient Populations

por QQJun 20th 2019

excellent course.\n\nThe first MOOC on computational pheonotying

por ABMay 13th 2019

This is a well-presented course. I highly recommend.

Instrutores

Avatar

Laura K. Wiley, PhD

Assistant Professor
Division of Biomedical Informatics and Personalized Medicine, 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 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.

  • Unfortunately at this time we can only allow students who have access to Google services (e.g., a gmail account) to complete the specialization. This is because we give students access to real clinical data and our privacy protections only allow data sharing through the Google BigQuery environment.

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.