中Artificial intelligence (AI) and machine learning (ML) have the potential to increase diagnostic accuracy, decrease diagnostic errors, and improve patient outcomes. The Data Augmented, Technology Assisted Medical Decision Making (DATA-MD) course will teach you how to use AI to augment your diagnostic decision-making. The National Academy of Medicine (NAM) recommends ensuring that clinicians can effectively use technology - including AI - to improve the diagnostic process. To use these technologies effectively in your clinical practice, you will need to determine when use of AI is appropriate, interpret the outputs of AI, read medical literature about AI, and explain to patients the role that AI plays in their care. In this course, you’ll explore the ethical considerations and potential biases when making medical decisions informed by AI/ML-based technologies. DATA-MD is a one of a kind curriculum designed to provide an introduction to the use of AI in the diagnostic process.
您将学到什么
Describe the crucial role, strengths, limitations of AI and ML in evidence-based medical decision making
Evaluate machine learning studies for bias and systematic error to enhance diagnostic decisions.
Apply the results of machine learning studies and outputs to diagnostic decisions.
Identify legal and ethical issues and best practices for AI and ML use in healthcare settings
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18 项作业
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该课程共有4个模块
In week 1, you will be introduced to artificial intelligence (AI) and machine learning (ML) and the vocabulary necessary to effectively communicate with relevant stakeholders. You will learn about some of the applications of AI/ML in healthcare and the challenges associated with using these technologies in healthcare.
涵盖的内容
17个视频6篇阅读材料5个作业1个讨论话题
In Module 2 you will learn the concepts and statistical measures necessary for interpretation of results of diagnostic studies that include ML.
涵盖的内容
15个视频3篇阅读材料5个作业1个讨论话题
In Module 3, you will develop the skills necessary to critically evaluate diagnostic studies that include AI/ML. This week emphasizes the skills necessary to efficiently and effectively use AI/ML to augment diagnostic decisions. step.
涵盖的内容
14个视频3篇阅读材料2个作业1个讨论话题
In the final Module of this course, you will review the current legal and ethical landscape of AI/ML in medicine, possible social biases that may be perpetuated by AI/ML algorithms, and recommendations for avoiding these.
涵盖的内容
15个视频4篇阅读材料6个作业1个讨论话题
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