Machine Learning Fundamentals for Healthcare

Machine learning and artificial intelligence have the potential to transform healthcare and open up a world of incredible possibilities. But we will never realize the potential of these technologies unless all stakeholders have a basic understanding of healthcare and machine learning concepts and principles. This course will introduce you to the fundamental concepts and principles of machine learning as they apply to medicine and healthcare. We will cover machine learning approaches, medical use cases, metrics unique to healthcare, and best practices for designing, building, and evaluating machine learning applications in healthcare. The course will provide individuals with non-engineering backgrounds in healthcare, medical policy, pharmaceutical development, and data science with the knowledge needed to critically evaluate and use these technologies. Co-author: Jeffrey Angus Editors: Mars Huang Jin Long Shannon Crawford Auge Marques In support of improving the patient experience, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Accreditation Center (ANCC) to provide continuing education for the healthcare team. Visit the FAQs below for important information regarding: 1) Issue and expiration dates; 2) Statements of accreditation and assignment of credit status; 3) Disclosure of information on financial relations for each person controlling the content of the activity.