AI in Healthcare Capstone

所在平台: Coursera

课程主页: https://www.coursera.org/learn/ai-in-healthcare-capstone

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课程简介

课程名称:医疗保健中的人工智能顶点项目 课程概述:本顶点项目带您深入探讨我们在不同课程中学到的所有概念。整个体验围绕一个患者的旅程展开,该患者出现呼吸症状,并因COVID-19的担忧寻求初级保健提供者的帮助。我们将从每次接触中产生的数据的角度跟踪患者的旅程,并使用为本专业特别创建的独特去标识数据集。该数据集涵盖电子健康记录(EHR)和图像数据,我们将利用这些数据集构建模型,以实现对患者的风险分层决策。我们将回顾不同选择(例如特征构建、数据类型的使用、模型评估的设置以及如何处理患者时间线)对模型推荐的护理影响。在这一探索过程中,我们还将讨论在使用人工智能帮助我们做出更好的护理决策时所遇到的监管和伦理问题。本课程将为医疗数据挖掘者提供实践经验。 课程大纲: - 第一部分:入门,第一阶段:数据收集 - 第二部分:第二阶段:模型训练第一部分 - 第三部分:第三阶段:模型训练第二部分 - 第四部分:第四阶段:模型评估 - 第五部分:第五阶段:模型部署与监管,总结 斯坦福大学医学院获得继续医学教育认证委员会(ACCME)的认证,以提供医生的继续医学教育。请参阅以下常见问题,以获取有关原始发布日期、终止或到期日期、认证和学分指定声明、以及每位参与活动内容控制人员的财务关系披露的重要信息。

课程大纲

Part: 1

Title:Getting Started, Phase 1: Data Collection

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Part: 2

Title:Phase 2: Model Training Part 1

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Part: 3

Title:Phase 3: Model Training Part 2

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Part: 4

Title:Phase 4: Model Evaluation

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Part: 5

Title:Phase 5: Model Deployment and Regulation, Wrap Up

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课程详情

This capstone project takes you on a guided tour exploring all the concepts we have covered in the different classes up till now. We have organized this experience around the journey of a patient who develops some respiratory symptoms and given the concerns around COVID19 seeks care with a primary care provider. We will follow the patient's journey from the lens of the data that are created at each encounter, which will bring us to a unique de-identified dataset created specially for this specialization. The data set spans EHR as well as image data and using this dataset, we will build models that enable risk-stratification decisions for our patient. We will review how the different choices you make -- such as those around feature construction, the data types to use, how the model evaluation is set up and how you handle the patient timeline -- affect the care that would be recommended by the model. During this exploration, we will also discuss the regulatory as well as ethical issues that come up as we attempt to use AI to help us make better care decisions for our patient. This course will be a hands-on experience in the day of a medical data miner. 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.

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