Stanford University
AI in Healthcare Specialization
58,768 enrolled
Stanford University

AI in Healthcare Specialization

Get in-depth knowledge of a subject

(2,184 reviews)

Beginner level
No prior experience required
Flexible schedule
1 month at 10 hours a week
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject

(2,184 reviews)

Beginner level
No prior experience required
Flexible schedule
1 month at 10 hours a week
Earn a career credential
Share your expertise with employers

Overview

  • 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

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English
90 practice exercises

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

Specialization - 5 course series

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: Health Systems
Category: Medicare
Category: Health Policy
Category: Hospital Medicine
Category: Medical Billing and Coding
Category: Health Care
Category: Healthcare Ethics
Category: Health Equity
Category: Healthcare Industry Knowledge
Category: Health Care Administration
Category: Health Disparities
Category: Pharmaceuticals
Category: Continuous Quality Improvement (CQI)
Category: Innovation

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: Data Mining
Category: Clinical Data Management
Category: Feature Engineering
Category: Clinical Research
Category: Electronic Medical Record
Category: Medical Records
Category: Health Informatics
Category: Text Mining
Category: Medical Imaging
Category: Data Collection
Category: Health Information Management
Category: Unstructured Data
Category: Data Ethics

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 Algorithms
Category: Machine Learning
Category: Applied Machine Learning
Category: Health Informatics
Category: Supervised Learning
Category: Data Processing
Category: Unstructured Data
Category: Predictive Modeling
Category: Artificial Neural Networks
Category: Deep Learning
Category: Healthcare Industry Knowledge
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: 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

Category: Application Deployment
Category: Regulatory Compliance
Category: Artificial Intelligence
Category: Healthcare Ethics
Category: Machine Learning
Category: Healthcare Industry Knowledge
Category: Health Care Procedure and Regulation
Category: Continuous Monitoring
Category: Data Ethics
Category: Health Systems
Category: Predictive Modeling
Category: Health Informatics
Category: Health Technology

What you'll learn

Skills you'll gain

Category: Image Analysis
Category: Applied Machine Learning
Category: Data Integrity
Category: Healthcare Industry Knowledge
Category: Health Assessment
Category: Data Ethics
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Application Deployment
Category: Health Care Procedure and Regulation
Category: Regulatory Compliance
Category: Health Informatics
Category: Clinical Data Management
Category: Data Collection
Category: Performance Tuning

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Matthew Lungren
Stanford University
2 Courses39,247 learners
Serena Yeung
Stanford University
2 Courses39,247 learners
Mildred Cho
Stanford University
2 Courses83,489 learners
Tina Hernandez-Boussard
Stanford University
2 Courses27,591 learners

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