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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/clinical-predictive-modeling
课程评论：没有评论
课程名称：预测建模与临床实践转型 课程概述：本课程教授如何利用预测模型转型临床实践的基本知识。课程重点探讨临床数据科学家在开发预测模型时必须注意的具体挑战和实施方法。 课程大纲： 1. 部分一：介绍：临床预测模型 描述：学习现有的多种类型的临床预测模型及其实际应用。 2. 部分二：工具：确保模型可用性 描述：了解如何运用定性方法开发更有可能转型临床实践的临床预测模型。 3. 部分三：技术：模型实施与可持续性 描述：学习用于在实践中实施临床预测模型的不同工具及影响实施时间的因素。 4. 部分四：技术：数据选择、模型构建与评估 描述：理解不同类型的临床数据如何在预测模型中使用，以及模型构建过程中做出的选择如何影响其实际效用。 5. 部分五：实际应用：开发临床预测模型 描述：将新技能付诸实践，开发一个对重症监护病房（ICU）住院期间死亡风险进行评估的临床预测模型。
Part: 1
Title:Introduction: Clinical Prediction Models
Description:Learn about the many types of clinical prediction models that exist and how they are put into practice.
Part: 2
Title:Tools: Ensuring Model Usability
Description:Understand how qualitative methods can be used to develop clinical prediction models that are more likely to transform clinical practice.
Part: 3
Title:Techniques: Model Implementation and Sustainability
Description:Learn about the different tools that are used to implement clinical prediction models in practice and the factors that affect implementations over time.
Part: 4
Title:Techniques: Data Selection, Model Building, and Evaluation
Description:Understand how the different types of clinical data can be used in prediction models and learn how choices made during model construction affect the utility of the model in practice.
Part: 5
Title:Practical Application: Developing a Clinical Prediction Model
Description:Put your new skills to the test - develop a clinical prediction model to asses risk of death during a stay in an Intensive Care Unit (ICU) stay.
This course teaches you the fundamentals of transforming clinical practice using predictive models. This course examines specific challenges and methods of clinical implementation, that clinical data scientists must be aware of when developing their predictive models.
