What you'll learn
Reinforce first principles of AI in health care from the previous course or from other related courses.
Discuss how large language models can dn have been applied in health care
Understand the process of forming and managing data science teams in health care
Explain the workflow of using CNNs for image classification
Discuss how AI can be used to solve clinical problems
Describe the process of successfully implementing AI projects in large health care organizations
The field of artificial intelligence has now begun to mature in many industries. Health care, however, still struggles to unlock the gains that these powerful technologies can provide. At the same time, health systems worldwide are struggling with aging populations, rising expectations, and ballooning costs. Innovation with AI in Health Care will give you a map to deal with these issues and transform your organization into an innovative, 21st century institution.
A barrier to the adoption of AI in health care is a lack of awareness amongst health care leaders. Many do not understand both the technical concepts of AI and the art of implementing these technologies successfully and at scale. The result is that the potential of AI to deliver value to patients, clinicians, and health care organizations is not realized, and precious resources are wasted in unsuccessful implementations. This course will teach the foundations of applied artificial intelligence from a business perspective and help provide key intuition for decision makers to lessen those missteps.
Innovation with AI in Health Care will help leaders of health care organizations develop the skills needed to realize the value of AI in health care and advance their careers through demonstrating leadership in digital transformation of health care. It also brings together a diverse community of leaders from the technical, clinical, and business worlds. This collective of the world’s largest technology and health care organizations will share their experiences—both positive and negative—of developing and implementing AI solutions in health care.
Participants will also be exposed to cutting-edge issues in health care AI, such as regulation. Short interactive projects carried out during the course will help reinforce key concepts and allow for small-group networking with other participants. There is an emphasis on group work, social learning, and establishing an international network of students who actively collaborate during—and especially after—the course.
This is the second course in the Business Applications for AI in Health Care Certificate of Specialization, which builds on the first program—AI for Health Care: Concepts and Applications. Both courses can be taken independently; however, the certificate program requires that both courses are taken. Without a strong background, it is recommended that you take AI for Health Care: Concepts and Applications before Innovation with AI in Health Care. It is also recommended that participants take the courses in order, as AI for Health Care: Concepts and Applications covers more foundational concepts upon which Innovation with AI in Health Care builds.
Both courses in the certificate are suitable for participants who have taken previous iterations of “Applied AI in Healthcare.” The speed at which AI is developing means that some of the core lessons and insights have updated slightly. The new group projects will also encourage engagement of the material in a collaborative, problem-driven setting. Some of the material in both courses does overlap with previous iterations, but this should serve as a useful refresher—participants can review the course agenda if interested in details.