課程信息
專項課程

第 2 門課程(共 6 門)

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
中級

中級

完成時間(小時)

完成時間大約為21 小時

建議:5 weeks of study, 2-4 hours/week...
可選語言

英語(English)

字幕:英語(English)
專項課程

第 2 門課程(共 6 門)

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
中級

中級

完成時間(小時)

完成時間大約為21 小時

建議:5 weeks of study, 2-4 hours/week...
可選語言

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 4 小時

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. ...
Reading
9 個視頻 (總計 54 分鐘), 4 個閱讀材料, 1 個測驗
Video9 個視頻
Clinical Research Data Warehouses9分鐘
Entity Relationship Diagrams (ERDs)4分鐘
Clinical Data Models4分鐘
Why Common Data Models?10分鐘
A Quick Tour of a Common Data Model: i2b26分鐘
A Quick Tour of a Common Data Model: OMOP5分鐘
A Quick Tour of a Common Data Model: Sentinel6分鐘
A Quick Tour of a Common Data Model: PCORNet5分鐘
Reading4 個閱讀材料
Introduction to Specialization Instructors5分鐘
Course Policies5分鐘
Accessing Course Data and Technology Platform15分鐘
Readings and Course Materials for Module 1
Quiz1 個練習
Clinical Data Models and Common Data Models30分鐘
2
完成時間(小時)
完成時間為 3 小時

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....
Reading
6 個視頻 (總計 59 分鐘), 1 個閱讀材料, 1 個測驗
Video6 個視頻
Querying MIMIC-III9分鐘
A Deep Dive into OMOP Data Model13分鐘
Querying OMOP12分鐘
Comparing the MIMIC and OMOP Data Models10分鐘
The OHDSI Community Ecosystem7分鐘
Reading1 個閱讀材料
Readings and Course Materials for Module 230分鐘
Quiz1 個練習
Tools: Querying Clinical Data Models30分鐘
3
完成時間(小時)
完成時間為 3 小時

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. ...
Reading
6 個視頻 (總計 53 分鐘), 1 個閱讀材料, 1 個測驗
Video6 個視頻
Structural versus Terminology Mapping6分鐘
Data Profiling with White Rabbit10分鐘
Data Mapping with the Rabbit in a Hat Tool9分鐘
Terminology Mapping10分鐘
Example mapping of MIMIC Patient to OMOP Person8分鐘
Reading1 個閱讀材料
Readings and Course Materials for Module 3
Quiz1 個練習
Techniques: Extract-Transform-Load and Terminology Mapping30分鐘
4
完成時間(小時)
完成時間為 3 小時

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....
Reading
5 個視頻 (總計 52 分鐘), 1 個閱讀材料, 1 個測驗
Video5 個視頻
Data profiling for data quality assessment10分鐘
Data quality assessment using SQL13分鐘
Callahan and Khare rules8分鐘
OHDSI Achilles and Achilles Heel12分鐘
Reading1 個閱讀材料
Readings and Course Materials for Module 430分鐘
Quiz1 個練習
Techniques: Data Quality Assessments30分鐘

講師

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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

關於 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....

關於 Clinical Data Science 專項課程

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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