Predictive analytics has a longstanding tradition in medicine. Developing better prediction models is a critical step in the pursuit of improved health care: we need these tools to guide our decision-making on preventive measures, and individualized treatments. In order to effectively use and develop these models, we must understand them better. In this course, you will learn how to make accurate prediction tools, and how to assess their validity. First, we will discuss the role of predictive analytics for prevention, diagnosis, and effectiveness. Then, we look at key concepts such as study design, sample size and overfitting.
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Population Health: Predictive Analytics
Лейденский университетОб этом курсе
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Гибкие сроки
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Средний уровень
Basic familiarity with R, knowledge of basic statistical concepts. Completing 'Population Health: Responsible Data Analysis' beforehand recommended.
Прибл. 18 часов на выполнение
Английский
Субтитры: Английский
Чему вы научитесь
Understand the role of predictive analytics for prevention, diagnosis, and effectiveness
Explain key concepts in prediction modelling: appropriate study design, adequate sample size and overfitting
Understand important issues in model development, such as missing data, non-linear relations and model selection
Know about ways to assess model quality through performance measures and validation
Приобретаемые навыки
Predictive Analyticsmedical statisticsR ProgrammingRegression Analysis
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Средний уровень
Basic familiarity with R, knowledge of basic statistical concepts. Completing 'Population Health: Responsible Data Analysis' beforehand recommended.
Прибл. 18 часов на выполнение
Английский
Субтитры: Английский
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Лейденский университет
Leiden University is one of Europe's foremost research universities. This prominent position gives our graduates a leading edge and prepares them for careers both within and outside of academia. Leiden University is the oldest university in the Netherlands, founded in 1575. Our motto is: Praesidium Libertatis (Bastion of Liberty) - Freedom of spirit, thought and expression. Leiden University has a campus in Leiden and The Hague, with 7 faculties, 47 Bachelor Programmes, 79 Master Programmes and nearly 30,000 students.
Программа курса: что вы изучите
2 ч. на завершение
Welcome to Leiden University
Welcome to the course Predictive Analytics! We are excited to have you in class and look forward to your contributions to the learning community. To begin, we recommend taking a few minutes to explore the course site. Review the material we will cover each week, and preview the assignments you will need to complete in order to pass the course. Click Discussions to see forums where you can discuss the course material with fellow students taking the class. If you have questions about course content, please post them in the forums to get help from others in the course community. For technical problems with the Coursera platform, visit the Learner Help Center.
2 ч. на завершение
2 видео ((всего 7 мин.)), 6 материалов для самостоятельного изучения
3 ч. на завершение
Prediction for prevention, diagnosis, and effectiveness
In this module, we discuss the role of predictive analytics for prevention, diagnosis, and effectiveness. We begin with a brief introduction to predictive analytics, which we follow by differentiating between population-based and targeted interventions. We then explain why and when it may be beneficial to test for a diagnosis, and how analytic tools can help inform these decisions. Finally, we focus on the balance between benefits and harms of a certain treatment, and how we can predict the benefit for an individual.
3 ч. на завершение
6 видео ((всего 28 мин.))
4 ч. на завершение
Modeling Concepts
In this module, we will present some key concepts in prediction modeling. First, we weigh the strengths and weakness of various study designs. Second, we stress the importance of an appropriate sample size for reliable inference. Then, we discuss the issues of overfitting a prediction model, and regression-to-the-mean. Finally, we will guide you through the popular bootstrap procedure, showing how it can be used to assess parameter variability.
4 ч. на завершение
6 видео ((всего 30 мин.)), 3 материалов для самостоятельного изучения, 3 тестов
4 ч. на завершение
Model development
In this module, we focus on model development. First, we turn our attention to the missing values problem. We discuss well-known missingness mechanisms, and methods to deal with missing values appropriately. Second, we learn about methods to deal with non-linearity in a dataset. We then address the topic of model selection, focusing on the limitations of traditional stepwise selection procedures. Last, we talk about how introducing bias in exchange for lower variance can improve prediction quality. This can be done by using advanced methods, such as LASSO and Ridge regression.
4 ч. на завершение
6 видео ((всего 30 мин.)), 4 материалов для самостоятельного изучения, 2 тестов
6 ч. на завершение
Model validation and updating
In this final module, we learn about assessing the quality of a prediction model. First, we extensively discuss standard performance measures for both binary and continuous outcomes. Second, we explore different ways of validating a prediction model. We look at how to assess both the internal, and the more relevant external validity of a model. Next, we will look at how to update a model and make it applicable to a specific medical setting. We conclude with an interview, where we more broadly discuss the potential of predictive analytics by taking the example of the island of Aruba.
6 ч. на завершение
6 видео ((всего 33 мин.)), 2 материалов для самостоятельного изучения, 5 тестов
Рецензии
Лучшие отзывы о курсе POPULATION HEALTH: PREDICTIVE ANALYTICS
от партнера PP13 сент. 2020 г.
Provide lots of useful tips for practical deployment of predictive analytics and also some brief theoretical background. A very well presented course.
от партнера TS4 янв. 2021 г.
Helpful course for the ones wanting to discover and understand how predictive analytics can help you in approaching health-related issues.
от партнера FG6 янв. 2021 г.
Very Challenging and instructive enjoyed it thank you
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