课程信息
7,820

第 2 门课程(共 6 门)

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

根据您的日程表重置截止日期。

中级

完成时间大约为23 小时

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

英语(English)

字幕:英语(English)

第 2 门课程(共 6 门)

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

根据您的日程表重置截止日期。

中级

完成时间大约为23 小时

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

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
完成时间为 4 小时

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 个视频 (总计 54 分钟), 4 个阅读材料, 1 个测验
9 个视频
Clinical Research Data Warehouses9分钟
Entity Relationship Diagrams (ERDs)4分钟
Clinical Data Models4分钟
Why Common Data Models?10分钟
A Quick Tour of a Common Data Model: i2b26分钟
A Quick Tour of a Common Data Model: OMOP5分钟
A Quick Tour of a Common Data Model: Sentinel6分钟
A Quick Tour of a Common Data Model: PCORNet5分钟
4 个阅读材料
Introduction to Specialization Instructors5分钟
Course Policies5分钟
Accessing Course Data and Technology Platform15分钟
Readings and Course Materials for Module 1
1 个练习
Clinical Data Models and Common Data Models30分钟
2
完成时间为 3 小时

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 个视频 (总计 59 分钟), 1 个阅读材料, 1 个测验
6 个视频
Querying MIMIC-III9分钟
A Deep Dive into OMOP Data Model13分钟
Querying OMOP12分钟
Comparing the MIMIC and OMOP Data Models10分钟
The OHDSI Community Ecosystem7分钟
1 个阅读材料
Readings and Course Materials for Module 230分钟
1 个练习
Tools: Querying Clinical Data Models30分钟
3
完成时间为 3 小时

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 个视频 (总计 53 分钟), 1 个阅读材料, 1 个测验
6 个视频
Structural versus Terminology Mapping6分钟
Data Profiling with White Rabbit10分钟
Data Mapping with the Rabbit in a Hat Tool9分钟
Terminology Mapping10分钟
Example mapping of MIMIC Patient to OMOP Person8分钟
1 个阅读材料
Readings and Course Materials for Module 3
1 个练习
Techniques: Extract-Transform-Load and Terminology Mapping30分钟
4
完成时间为 3 小时

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 个视频 (总计 52 分钟), 1 个阅读材料, 1 个测验
5 个视频
Data profiling for data quality assessment10分钟
Data quality assessment using SQL13分钟
Callahan and Khare rules8分钟
OHDSI Achilles and Achilles Heel12分钟
1 个阅读材料
Readings and Course Materials for Module 430分钟
1 个练习
Techniques: Data Quality Assessments30分钟

讲师

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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

关于 科罗拉多大学系统

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

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