课程信息
专项课程

第 3 门课程(共 6 门)

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

Some programming experience in any language.

完成时间(小时)

完成时间大约为21 小时

建议:5 weeks of study, 2-4 hours/week...
可选语言

英语(English)

字幕:英语(English)

您将学到的内容有

  • 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.

专项课程

第 3 门课程(共 6 门)

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

Some programming experience in any language.

完成时间(小时)

完成时间大约为21 小时

建议:5 weeks of study, 2-4 hours/week...
可选语言

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 2 小时

Introduction: Identifying Patient Populations

Learn about computational phenotyping and how to use the technique to identify patient populations. ...
Reading
2 个视频 (总计 7 分钟), 9 个阅读材料, 2 个测验
Video2 个视频
Introduction to Computational Phenotyping5分钟
Reading9 个阅读材料
Introduction to Specialization Instructors5分钟
Course Policies5分钟
Accessing Course Data and Technology Platform15分钟
Introduction to Manual Record Review10分钟
Methods - Selecting Reviewers10分钟
Methods - Selecting Records for Review10分钟
Methods - Creating Review Instruments and Protocols10分钟
Methods - Assessing Review Quality10分钟
Introduction to Course Example15分钟
Quiz2 个练习
Week 1 Practice Quiz8分钟
Week 1 Assessment16分钟
2
完成时间(小时)
完成时间为 3 小时

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 个视频 (总计 19 分钟), 2 个阅读材料, 2 个测验
Video5 个视频
Computational Phenotyping: Billing Data5分钟
Computational Phenotyping: Laboratory Data3分钟
Computational Phenotyping: Clinical Observations2分钟
Computational Phenotyping: Medications3分钟
Reading2 个阅读材料
Testing Individual Data Types30分钟
Note about the Assessment2分钟
Quiz2 个练习
Programming Exercises Practice Quiz30分钟
Week 2 Assessment18分钟
3
完成时间(小时)
完成时间为 3 小时

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 个视频 (总计 15 分钟), 2 个阅读材料, 2 个测验
Video2 个视频
Combining Multiple Data Types5分钟
Reading2 个阅读材料
Data Manipulations30分钟
Data Combinations45分钟
Quiz2 个练习
Programming Exercises Practice Quiz30分钟
Week 3 Assessment25分钟
4
完成时间(小时)
完成时间为 1 小时

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 个视频 (总计 4 分钟), 1 个阅读材料, 1 个测验
Video1 个视频
Reading1 个阅读材料
Assessing Algorithmic Accuracy, Complexity, and Portability25分钟
Quiz1 个练习
Week 4 Assessment20分钟

讲师

Avatar

Laura K. Wiley, PhD

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

关于 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....

关于 Clinical Data Science 专项课程

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

常见问题

  • 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.

还有其他问题吗?请访问 学生帮助中心