Stanford University
AI in Healthcare Specialization
Stanford University

AI in Healthcare Specialization

Taught in English

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Matthew Lungren
Serena Yeung
Mildred Cho

Instructors: Matthew Lungren

35,266 already enrolled

Specialization - 5 course series

Get in-depth knowledge of a subject

4.7

(1,527 reviews)

Beginner level
No prior experience required
1 month at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Identify problems healthcare providers face that machine learning can solve

  • Analyze how AI affects patient care safety, quality, and research

  • Relate AI to the science, practice, and business of medicine

  • Apply the building blocks of AI to help you innovate and understand emerging technologies

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Specialization - 5 course series

Get in-depth knowledge of a subject

4.7

(1,527 reviews)

Beginner level
No prior experience required
1 month at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 5 course series

Introduction to Healthcare

Course 111 hours4.8 (914 ratings)

What you'll learn

  • The major challenges of the U.S.healthcare system

  • Issues you may encounter in efforts to improve healthcare delivery and the healthcare system

  • Who the key stakeholders are in the U.S. healthcare system

Introduction to Clinical Data

Course 211 hours4.7 (307 ratings)

What you'll learn

  • How to apply a framework for medical data mining

  • Ethical use of data in healthcare decisions

  • How to make use of data that may be inaccurate in systematic ways

  • What makes a good research question and how to construct a data mining workflow answer it

Fundamentals of Machine Learning for Healthcare

Course 314 hours4.8 (442 ratings)

What you'll learn

  • Define important relationships between the fields of machine learning, biostatistics, and traditional computer programming.

  • Learn about advanced neural network architectures for tasks ranging from text classification to object detection and segmentation.

  • Learn important approaches for leveraging data to train, validate, and test machine learning models.

  • Understand how dynamic medical practice and discontinuous timelines impact clinical machine learning application development and deployment.

Evaluations of AI Applications in Healthcare

Course 411 hours4.5 (222 ratings)

What you'll learn

  • Principles and practical considerations for integrating AI into clinical workflows

  • Best practices of AI applications to promote fair and equitable healthcare solutions

  • Challenges of regulation of AI applications and which components of a model can be regulated

  • What standard evaluation metrics do and do not provide

AI in Healthcare Capstone

Course 510 hours4.6 (198 ratings)

What you'll learn

Instructors

Matthew Lungren
Stanford University
2 Courses27,251 learners
Serena Yeung
Stanford University
2 Courses27,251 learners

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