enthaltenArtificial 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.
Empfohlene Erfahrung
Was Sie lernen werden
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
Kompetenzen, die Sie erwerben
- Kategorie: AI Law and Ethics
- Kategorie: AI for Diagnosis
- Kategorie: AI/ML Methodologies
- Kategorie: Medical Decision Making
Wichtige Details
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18 Aufgaben
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In diesem Kurs gibt es 4 Module
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.
Das ist alles enthalten
17 Videos6 Lektüren5 Aufgaben1 Diskussionsthema
In Module 2 you will learn the concepts and statistical measures necessary for interpretation of results of diagnostic studies that include ML.
Das ist alles enthalten
15 Videos3 Lektüren5 Aufgaben1 Diskussionsthema
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.
Das ist alles enthalten
14 Videos3 Lektüren2 Aufgaben1 Diskussionsthema
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.
Das ist alles enthalten
15 Videos4 Lektüren6 Aufgaben1 Diskussionsthema
Dozent
Empfohlen, wenn Sie sich für Machine Learning interessieren
University of Michigan
Johns Hopkins University
Johns Hopkins University
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