|
所在平台: Coursera |
课程主页: https://www.coursera.org/learn/introduction-clinical-data
课程评论：没有评论
课程名称：临床数据入门 课程概述：本课程为您提供成功且符合伦理的医学数据挖掘框架。我们将探索在医疗服务中收集的各种临床数据，学习构建可分析的数据集，并应用计算程序以回答临床问题。此外，我们还将探讨在利用医疗数据做出患者护理决策时可能出现的公平性和偏见问题。 该课程由斯坦福大学医学院提供，并获得了继续医学教育认证委员会（ACCME）的认证，允许其为医生提供继续医学教育。有关课程的重要信息，请查看FAQs，包括1）原始发布和终止或过期日期；2）认证和学分分配声明；3）对活动内容控制人员的财务关系披露。 课程大纲： - 第一部分：通过临床数据挖掘提出和回答问题 - 第二部分：来自医疗系统的数据 - 第三部分：临床数据挖掘中的时间表示及事件时机 - 第四部分：从患者时间线中创建可分析的数据集 - 第五部分：处理非结构化医疗数据：文本、图像、信号 - 第六部分：将各部分整合在一起：电子表型分析 - 第七部分：伦理问题 - 第八部分：课程总结 通过本课程，您将掌握如何有效利用临床数据来优化患者护理决策，同时关注道德和公正的问题。
Part: 1
Title:Asking and answering questions via clinical data mining
Description:
Part: 2
Title:Data available from Healthcare systems
Description:
Part: 3
Title:Representing time, and timing of events, for clinical data mining
Description:
Part: 4
Title:Creating analysis ready datasets from patient timelines
Description:
Part: 5
Title:Handling unstructured healthcare data: text, images, signals
Description:
Part: 6
Title:Putting the pieces together: Electronic phenotyping
Description:
Part: 7
Title:Ethics
Description:
Part: 8
Title:Course Conclusion
Description:
This course introduces you to a framework for successful and ethical medical data mining. We will explore the variety of clinical data collected during the delivery of healthcare. You will learn to construct analysis-ready datasets and apply computational procedures to answer clinical questions. We will also explore issues of fairness and bias that may arise when we leverage healthcare data to make decisions about patient care. The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. Visit the FAQs below for important information regarding 1) Date of original release and Termination or expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content.
