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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/deep-learning-methods-healthcare
课程评论：没有评论
课程名称：深度学习在医疗保健中的方法 课程概述：此课程涵盖了深度学习（DL）方法、医疗保健数据及其在医疗中的应用。课程包括视频讲座、自主编程实验、作业（书面和编程）以及一个大型项目。课程的第一阶段将通过视频讲座介绍不同的深度学习和健康应用主题，自主实验和多项作业。在这一阶段，您将积累在医疗保健数据上开发实用深度学习模型的知识和经验。课程的第二阶段将是一个大型项目，最终形成技术报告和深度学习模型的功能演示，旨在解决一些具体的医疗问题。我们期待最佳项目能够潜在地转化为科学出版物。 课程大纲： 第1部分 标题：第1周 - 嵌入 描述：课程概述及嵌入的相关内容。 第2部分 标题：第2周 - 卷积神经网络（CNN） 描述：讨论卷积和池化的重要性，并介绍卷积神经网络的相关信息。 第3部分 标题：第3周 - 循环神经网络（RNN） 描述：循环神经网络具有重要的构建模块。我们将解释这些模块并给出医疗保健应用的例子。 第4部分 标题：第4周 - 自编码器 描述：了解自编码器在机器学习中的不可或缺性，并展示其在医疗中的应用。
Part: 1
Title:Week 1 - Embedding
Description:An overview of the course and everything about Embedding.
Part: 2
Title:Week 2 - Convolutional Neural Networks (CNN)
Description:We discuss the importance of Convolution and Pooling, and then present relevant information about Convolutional Neural Networks.
Part: 3
Title:Week 3 - Recurrent Neural Networks (RNN)
Description:Recurrent Neural Network have important building blocks. We'll explain those and give examples for healthcare applications.
Part: 4
Title:Week 4 - Autoencoders
Description:Learn why Autoencoders are indispensible in Machine Learning. We'll also show you how this is applied in healthcare.
This course covers deep learning (DL) methods, healthcare data and applications using DL methods. The courses include activities such as video lectures, self guided programming labs, homework assignments (both written and programming), and a large project. The first phase of the course will include video lectures on different DL and health applications topics, self-guided labs and multiple homework assignments. In this phase, you will build up your knowledge and experience in developing practical deep learning models on healthcare data. The second phase of the course will be a large project that can lead to a technical report and functioning demo of the deep learning models for addressing some specific healthcare problems. We expect the best projects can potentially lead to scientific publications.
