Stanford University
AI in Healthcare Specialization
Stanford University

AI in Healthcare Specialization

Matthew Lungren
Serena Yeung
Mildred Cho

Instructors: Matthew Lungren

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4.7

(1,945 reviews)

Beginner level
No prior experience required
1 month
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.7

(1,945 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

Details to know

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Taught in English

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Stanford University
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Specialization - 5 course series

Introduction to Healthcare

Course 111 hours4.8 (1,169 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

Skills you'll gain

Category: Medicare
Category: Payment Systems
Category: Insurance
Category: Health Care Administration
Category: Billing Systems
Category: Healthcare Industry Knowledge
Category: Pharmaceuticals
Category: Ethical Standards And Conduct
Category: Business Ethics
Category: Quality Improvement
Category: Quality Assessment
Category: Health Systems
Category: Health Care Procedure and Regulation
Category: Health Care
Category: Performance Measurement
Category: Financial Systems
Category: Regulatory Affairs

Introduction to Clinical Data

Course 211 hours4.6 (410 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

Skills you'll gain

Category: Clinical Data Management
Category: Data Mining
Category: Feature Engineering
Category: Electronic Medical Record
Category: Data Collection
Category: Data Analysis
Category: Machine Learning
Category: Unstructured Data
Category: Image Analysis
Category: Data Ethics
Category: Text Mining
Category: Health Care
Category: Natural Language Processing
Category: Data Transformation

Fundamentals of Machine Learning for Healthcare

Course 314 hours4.8 (528 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.

Skills you'll gain

Category: Machine Learning
Category: Machine Learning Algorithms
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Predictive Modeling
Category: Reinforcement Learning
Category: Data Ethics
Category: Data Processing
Category: Applied Machine Learning
Category: Health Care Procedure and Regulation
Category: Natural Language Processing
Category: Image Analysis
Category: Supervised Learning
Category: Deep Learning
Category: Medical Science and Research
Category: Health Care
Category: Artificial Neural Networks

Evaluations of AI Applications in Healthcare

Course 411 hours4.5 (275 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

Skills you'll gain

Category: Artificial Intelligence
Category: Data Quality
Category: Patient Safety
Category: Data Ethics
Category: Predictive Modeling
Category: Clinical Data Management
Category: Regulatory Compliance
Category: Healthcare Industry Knowledge
Category: Application Deployment
Category: Machine Learning
Category: Health Assessment
Category: Health Care
Category: Decision Support Systems

AI in Healthcare Capstone

Course 510 hours4.7 (241 ratings)

What you'll learn

Skills you'll gain

Category: Machine Learning
Category: Predictive Modeling
Category: Applied Machine Learning
Category: Image Analysis
Category: Performance Tuning
Category: Risk Modeling
Category: Regulatory Compliance
Category: Machine Learning Software
Category: Feature Engineering
Category: Clinical Data Management
Category: Data Collection
Category: Healthcare Industry Knowledge
Category: Artificial Intelligence
Category: Health Care Procedure and Regulation
Category: Data Ethics

Instructors

Matthew Lungren
Stanford University
2 Courses34,147 learners
Serena Yeung
Stanford University
2 Courses34,147 learners

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