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

(2,300 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

(2,300 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

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

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

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

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

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

AI in Healthcare Capstone

Course 510 hours

What you'll learn

Skills you'll gain

Applied Machine Learning, Machine Learning, Risk Modeling, Artificial Intelligence, Responsible AI, Performance Tuning, Data Validation, Patient-centered Care, Application Deployment, Data Ethics, Healthcare Industry Knowledge, Feature Engineering, Health Informatics, Data Collection, Healthcare Ethics, Health Care Procedure and Regulation, Clinical Data Management, and Analysis

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Instructors

Matthew Lungren
Stanford University
2 Courses41,628 learners
Serena Yeung
Stanford University
2 Courses41,628 learners

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