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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/artificial-intelligence-for-breast-cancer-detection
课程评论：没有评论
课程名称：人工智能在乳腺癌检测中的应用 课程概述：本课程旨在让学生了解利用人工智能技术进行乳腺癌检测的各种处理方法。学生将通过测验和讨论会加强各模块中传达的关键概念，并将有阅读作业，包括期刊论文，以帮助理解模块主题。该课程适合对人工智能产品开发感兴趣的学生，特别是想要了解如何将人工智能应用于乳腺X光检查的学生。课程内容不仅侧重于人工智能的处理范式，还包括乳腺影像学的领域知识。 本课程的独特之处在于为学生提供广泛的人工智能视角，而不是仅关注某种特定的实现方法。完成本课程的学生将能够将所学知识应用于人工智能领域的入门级职位，并在项目中表现出色，因为他们对人工智能处理范式有深入的理解。 课程大纲： 1. 乳腺癌与乳腺影像简介 - 描述：在模块1中，您将了解乳腺癌的流行病学及其影像学方法。 2. 人工智能简介 - 描述：在模块2中，我们将介绍人工智能的历史、关键要素和方法，并定义人工智能分类性能的评估方法。 3. 乳腺X光检查中常见的异常 - 描述：在本模块中，我们将回顾乳腺影像中常见的异常，为思考如何利用人工智能进行检测打下基础。 4. 人工智能在乳腺癌检测中的应用 - 描述：在本模块中，我们将探讨两种主要的人工智能方法，这些方法适用于乳腺癌的检测。
Name:Introduction to Breast Cancer and Breast Imaging
Description:In module 1, you will be introduced to breast cancer epidemiology and approaches to breast cancer imaging.
Name:Introduction of Artificial Intelligence
Description:In Module 2, we will introduce the history of AI and the key elements and approaches. We will also define the assessment methods of AI classification performance
Name:Mammographic Abnormalities
Description:In this module, we will review common abnormalities identified on breast imaging in order to pave the way to thinking about using AI in detection.
Name:AI Applications to Breast Cancer Detection
Description:In this module, we will explore two major AI approaches which are applicable to the breast cancer detection.
The objective of this course is to provide students the knowledge of artificial intelligence processing approaches to breast cancer detection. Students will take quizzes and participate in discussion sessions to reinforce critical concepts conveyed in the modules. Reading assignments, including journal papers to understand the topics in the modules, will be provided. The course is designed for students who are interested in the career of product development using artificial intelligence and would like to know how AI can be applied to mammography. The course content is focused on the AI processing paradigm along with the domain knowledge of breast imaging. This course approach is unique, providing students a broad perspective of AI, rather than homing in on a particular implementation method. Students who complete this course will not only leverage the knowledge into an entry level job in the field of artificial intelligence but also perform well on projects because their thorough understanding of the AI processing paradigm.
