Stanford University
AI in Healthcare Specialization
Stanford University

AI in Healthcare Specialization

Matthew Lungren
Serena Yeung
Mildred Cho

Instructors: Matthew Lungren

Get in-depth knowledge of a subject
4.7

(2,303 reviews)

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

(2,303 reviews)

Beginner level
No prior experience required
4 weeks to complete
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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Taught in English
90 practice exercises

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Specialization - 5 course series

Introduction to Healthcare

Introduction to Healthcare

Course 111 hours

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

Health Policy, Health Care, Medicare, Medicaid, Healthcare Industry Knowledge, Managed Care, Health Care Administration, Health Care Procedure and Regulation, Hospital Experience, Pharmaceuticals, Value-Based Care, Medical Billing, Health Systems, and Healthcare Ethics

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

Clinical Data Management, Electronic Medical Record, Feature Engineering, Data Mining, Clinical Research, Data Collection, Unstructured Data, Health Informatics, Data Processing, Health Care, Data Ethics, Medical Imaging, Data Transformation, and Text Mining

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

Machine Learning, Machine Learning Algorithms, Medical Science and Research, Deep Learning, Health Policy, Data Ethics, Supervised Learning, Responsible AI, Artificial Neural Networks, Applied Machine Learning, Healthcare Ethics, Healthcare Industry Knowledge, Health Informatics, Reinforcement Learning, Data Processing, Artificial Intelligence and Machine Learning (AI/ML), and Health Care

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

Responsible AI, Regulatory Compliance, AI Personalization, Health Informatics, Data Ethics, Health Technology, Application Deployment, Decision Support Systems, Clinical Research Ethics, Healthcare Industry Knowledge, Health Equity, Clinical Informatics, Clinical Assessment, Predictive Modeling, and Continuous Monitoring
AI in Healthcare Capstone

AI in Healthcare Capstone

Course 510 hours

What you'll learn

Skills you'll gain

Applied Machine Learning, Risk Modeling, Responsible AI, Performance Tuning, Application Deployment, Data Ethics, Data Collection, Clinical Data Management, Health Informatics, Health Care Procedure and Regulation, Artificial Intelligence and Machine Learning (AI/ML), Feature Engineering, Healthcare Industry Knowledge, and Healthcare Ethics

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Instructors

Matthew Lungren
Stanford University
2 Courses41,812 learners
Serena Yeung
Stanford University
2 Courses41,812 learners

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