Об этом курсе
Специализация

Курс 3 из 6 в программе

100% онлайн

100% онлайн

Начните сейчас и учитесь по собственному графику.
Гибкие сроки

Гибкие сроки

Назначьте сроки сдачи в соответствии со своим графиком.
Промежуточный уровень

Промежуточный уровень

Some programming experience in any language.

Часов на завершение

Прибл. 21 час на выполнение

Предполагаемая нагрузка: 5 weeks of study, 2-4 hours/week...
Доступные языки

Английский

Субтитры: Английский

Чему вы научитесь

  • 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.

Специализация

Курс 3 из 6 в программе

100% онлайн

100% онлайн

Начните сейчас и учитесь по собственному графику.
Гибкие сроки

Гибкие сроки

Назначьте сроки сдачи в соответствии со своим графиком.
Промежуточный уровень

Промежуточный уровень

Some programming experience in any language.

Часов на завершение

Прибл. 21 час на выполнение

Предполагаемая нагрузка: 5 weeks of study, 2-4 hours/week...
Доступные языки

Английский

Субтитры: Английский

Программа курса: что вы изучите

Неделя
1
Часов на завершение
2 ч. на завершение

Introduction: Identifying Patient Populations

Learn about computational phenotyping and how to use the technique to identify patient populations. ...
Reading
2 видео ((всего 7 мин.)), 9 материалов для самостоятельного изучения, 2 тестов
Video2 видео
Introduction to Computational Phenotyping5мин
Reading9 материалов для самостоятельного изучения
Introduction to Specialization Instructors5мин
Course Policies5мин
Accessing Course Data and Technology Platform15мин
Introduction to Manual Record Review10мин
Methods - Selecting Reviewers10мин
Methods - Selecting Records for Review10мин
Methods - Creating Review Instruments and Protocols10мин
Methods - Assessing Review Quality10мин
Introduction to Course Example15мин
Quiz2 практических упражнения
Week 1 Practice Quiz8мин
Week 1 Assessment16мин
Неделя
2
Часов на завершение
3 ч. на завершение

Tools: Clinical Data Types

Understand how different clinical data types can be used to identify patient populations. Begin developing a computational phenotyping algorithm to identify patients with type II diabetes....
Reading
5 видео ((всего 19 мин.)), 2 материалов для самостоятельного изучения, 2 тестов
Video5 видео
Computational Phenotyping: Billing Data5мин
Computational Phenotyping: Laboratory Data3мин
Computational Phenotyping: Clinical Observations2мин
Computational Phenotyping: Medications3мин
Reading2 материала для самостоятельного изучения
Testing Individual Data Types30мин
Note about the Assessment2мин
Quiz2 практических упражнения
Programming Exercises Practice Quiz30мин
Week 2 Assessment18мин
Неделя
3
Часов на завершение
3 ч. на завершение

Techniques: Data Manipulations and Combinations

Learn how to manipulate individual data types and combine multiple data types in computational phenotyping algorithms. Develop a more sophisticated computational phenotyping algorithm to identify patients with type II diabetes....
Reading
2 видео ((всего 15 мин.)), 2 материалов для самостоятельного изучения, 2 тестов
Video2 видео
Combining Multiple Data Types5мин
Reading2 материала для самостоятельного изучения
Data Manipulations30мин
Data Combinations45мин
Quiz2 практических упражнения
Programming Exercises Practice Quiz30мин
Week 3 Assessment25мин
Неделя
4
Часов на завершение
1 ч. на завершение

Techniques: Algorithm Selection and Portability

Understand how to select a single "best" computational phenotyping algorithm. Finalize and justify a phenotyping algorithm for type II diabetes....
Reading
1 видео ((всего 4 мин.)), 1 материал для самостоятельного изучения, 1 тест
Video1 видео
Reading1 материал для самостоятельного изучения
Assessing Algorithmic Accuracy, Complexity, and Portability25мин
Quiz1 практическое упражнение
Week 4 Assessment20мин

Преподаватель

Avatar

Laura K. Wiley, PhD

Assistant Professor
Division of Biomedical Informatics and Personalized Medicine, Anschutz Medical Campus

О 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....

О специализации ''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

Часто задаваемые вопросы

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • 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.

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