About this Course
최근 조회 8,129

다음 전문 분야의 6개 강좌 중 2번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

영어

자막: 영어

다음 전문 분야의 6개 강좌 중 2번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 4시간 필요

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 videos (Total 54 min), 4 readings, 1 quiz
9개의 동영상
Clinical Data Models4m
Why Common Data Models?10m
A Quick Tour of a Common Data Model: i2b26m
A Quick Tour of a Common Data Model: OMOP5m
A Quick Tour of a Common Data Model: Sentinel6m
A Quick Tour of a Common Data Model: PCORNet5m
4개의 읽기 자료
Introduction to Specialization Instructors5m
Course Policies5m
Accessing Course Data and Technology Platform15m
Readings and Course Materials for Module 12h
1개 연습문제
Clinical Data Models and Common Data Models30m
2
완료하는 데 3시간 필요

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 videos (Total 59 min), 1 reading, 1 quiz
6개의 동영상
Querying OMOP12m
Comparing the MIMIC and OMOP Data Models10m
The OHDSI Community Ecosystem7m
1개의 읽기 자료
Readings and Course Materials for Module 21시 30분
1개 연습문제
Tools: Querying Clinical Data Models30m
3
완료하는 데 3시간 필요

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 videos (Total 53 min), 1 reading, 1 quiz
6개의 동영상
Data Mapping with the Rabbit in a Hat Tool9m
Terminology Mapping10m
Example mapping of MIMIC Patient to OMOP Person8m
1개의 읽기 자료
Readings and Course Materials for Module 32h
1개 연습문제
Techniques: Extract-Transform-Load and Terminology Mapping30m
4
완료하는 데 3시간 필요

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 videos (Total 52 min), 1 reading, 1 quiz
5개의 동영상
Callahan and Khare rules8m
OHDSI Achilles and Achilles Heel12m
1개의 읽기 자료
Readings and Course Materials for Module 41시 30분
1개 연습문제
Techniques: Data Quality Assessments30m

강사

Avatar

Laura K. Wiley, PhD

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

Michael G. Kahn, MD, PhD

Professor of Clinical Informatics
Department of Pediatrics, Anschutz Medical Campus

콜로라도 대학교 정보

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....

Clinical Data Science 전문 분야 정보

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

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.