AI in Health Care: From Strategies to Implementation

  • Executive Education
Overlapping collage of x-rays.
Register Now

-

Registration Deadline: June 26

Deadline Approaching Enroll now to secure your seat.

This two-month online program is designed to equip health care leaders with the knowledge and strategies to design, pitch, and implement AI-driven solutions and bring about transformative change in their organizations.

  • Online; Instructor-Paced

Self-paced learning complemented by live sessions with faculty and weekly office hours conducted by program leaders.

$2,900

Flexible payment and team-based learning options are available.

Certificate

Upon completion of this program, you will receive a digital certificate from Harvard Medical School.

8 Weeks, 4-6 Hours/Week

Each week you will engage with recorded video lectures from faculty, attend webinars and office hours, complete quizzes and required activities, engage in moderated discussion groups with, and work on your final project, if required.

On This Page

Overview

The eight-week online AI in Health Care: From Strategies to Implementation program is designed to equip health care leaders with the knowledge and strategies to design, pitch and implement AI-driven solutions and bring about transformative change in their organizations. The program’s curriculum prepares leaders to make informed decisions and envision strategic AI implementation in the unique cultural, economic and regulatory context of health care.

Learning Objectives

  • Evaluate existing AI systems in health care to understand their strengths and weaknesses.
  • Identify new opportunities for AI in health care to address unmet needs.
  • Assess the ethical implications and potential biases of AI technologies in health care settings.
Executive Education Logo Executive Education

Participant Types

Business leaders who are responsible for strategic decisions about AI-enabled initiatives in the health care or life sciences industry.

About the Program

Guided by expert Harvard Medical School faculty and guest speakers, develop a deep understanding of real-world data, digital medicine, and AI applications, and learn to translate AI concepts into actionable success. 

Curriculum

Through case studies, real-world examples, and a capstone project, you will gain the skills needed to frame a machine learning solution for a health care challenge, evaluate and select appropriate AI models, and implement AI strategies from end to end. Explain the fundamentals of modern methods in AI, including the role of data and computing in building successful AI applications.

The capstone project is a core component of your readiness to implement AI in a real-world health care setting. The project will require you to ideate and pitch a new AI-first health care solution that addresses an unmet need. Your project will span the course of the program, enabling you to incorporate the concepts and frameworks you learn in each module to develop your pitch.

This Harvard Medical School Executive Education program is taught by HMS faculty and is promoted by Emeritus. Emeritus is responsible for advertising, marketing, registration, and collecting payment.

Questions?

Contact one of our program advisors at learner.success@emeritus.org.

Modules

AI has come a long way in a short amount of time. Examine its evolution, differentiate between supervised and self-supervised learning, and explore emerging AI applications in health care.

Creating and implementing an AI health care solution involves a careful balance of training, validation, and deployment. Explore each stage of the AI development pipeline and formulate an idea for an AI-driven health care solution that you will work on throughout the program to fulfill the capstone requirement.

Leveraging the power of AI in a health care setting can be challenging. Examine the complexities of developing successful AI-driven products for the health care industry and identify the factors that must be considered to create a successful product.

Risk prediction models assess the likelihood of a given outcome. Discover common evaluation measures used with these models and the level of certainty required for clinical decision-making.

The AI development pipeline offers a host of benefits, but it also introduces potential ethical concerns. Examine each pipeline stage through the lens of ethics and equip yourself with the knowledge to identify and avoid ethically problematic choices and practices throughout the development process.

AI implementation carries a unique set of considerations for startups. Guided by a leader in the AI startup world, learn to transform your idea for an AI-first health care solution into a compelling story and viable investor pitch.

Person-generated health data (PGHD) gathered by wearable devices and machine learning algorithms offer a wide range of new health care possibilities. Explore the advantages and disadvantages of leveraging machine learning to collect and assess wearable data and examine the role of community benchmarks and transparency in developing machine learning methods.

A viable pitch is instrumental to securing funding for an AI-first health care solution. Join the members of your cohort as some of them share pitches for their solutions and examine what makes an effective pitch and why.

Teaching Team

Andrew Beam.

Andrew Beam

PhD

  • Chief Technology Officer, Lila Sciences, Inc.
  • Associate Professor of Epidemiology, Harvard T.H. Chan School of Public Health
Luca Foschini.

Luca Foschini

PhD

  • Co-Founder and Chief Data Scientist, Evidation
Marzyeh Ghassemi.

Marzyeh Ghassemi

MSc, PhD

  • Assistant Professor, Computer Science and Medicine, University of Toronto
Lily Peng.

Lily Peng

MD, PhD

  • Group Product Manager, Google Health
Karandeep Singh headshot

Karandeep Singh

BS, MD, MMSc

  • Associate Professor in Biomedical Informatics, UC San Diego
  • Chief Health AI Officer, UC San Diego Health

Learner Stories and Insights

Program Topics