Innovation with AI in Health Care

Certificate of Specialization:Business Applications for AI in Health Care
  • Online
  • May 710, 2024
  • $2,600

Overview

AI in Health Care: Transforming Organizations Through Innovation

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.

Take the Next Step in Your Career Evolution with the
Business Applications for AI in Health Care Certificate of Specialization 

Innovation with AI in Health Care contributes to the Business Applications for AI in Health Care Certificate of Specialization, designed for all health care stakeholders, from the doctor’s office to the business suite. To obtain your Certificate, choose two of three online programs created and taught by Harvard Faculty and pioneers of AI in health care to prepare you for the future of an ever-changing health care industry.

For more information, visit our Business Applications for AI in Health Care Certificate of Specialization page.

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 program builds upon AI for Health care: Concepts and Applications. Both courses can be taken independently; however, to earn the Business Applications for AI in Health Care Certificate of Specialization, you must take two of three programs in our health care AI portfolio. Without a strong background in AI, it is recommended that you take AI for Health Care: Concepts and Applications before either Innovation with AI in Health Care or Implementing Health Care AI in Clinical Practice as AI for Health Care: Concepts and Applications covers more foundational concepts upon which the other two programs build. 

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.

Objectives & Highlights

  • 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
  • Identify future challenges and opportunities in generative AI

Credits and Logistics

Program Format

This program will be delivered online daily from 9-1:30, with slight timing variations, in a live, synchronous format. The faculty will also offer office hours, which will include an open Q+A and review of materials from the day.

Continuing Education Credit

Harvard T.H. Chan School of Public Health will grant 1.2 Continuing Education Units (CEUs) for this program, equivalent to 12 contact hours of education. Participants can apply these contact hours toward other professional education accrediting organizations.

All credits subject to final agenda.

Faculty

Current faculty, subject to change.

Heather Mattie, PhD, SM, MS

Program Director

May 710, 2024
Lecturer, Co-Director, Health Data Science Master’s Program, Director of EDIB Programs
Department of Biostatistics
Harvard T.H. Chan School of Public Health

Trishan Panch, MD, MPH

Program Director

May 710, 2024
Instructor
Harvard T.H. Chan School of Public Health

Co-Founder
Wellframe

Monica Agrawal

Faculty

May 710, 2024

John Brownstein, PhD

Faculty

May 710, 2024
Chief Innovation Officer
Adebona Account

Professor of Pediatrics
Harvard Medical School

Mohammad Jouni

Faculty

May 710, 2024
Chief Technology Officer
Wellframe

Emily Lindemer, PhD

Faculty

May 710, 2024

Gianluca Mauro

Faculty

May 710, 2024
CEO
AI Academy

Santiago Romero-Brufau, MD, PhD

Faculty

May 710, 2024
Director of AI and Systems Engineering
Department of Otolaryngology — Head and Neck Surgery
Mayo Clinic

Adjunct Assistant Professor
Department of Biostatistics
Harvard T.H. Chan School of Public Health

Agenda

May 7 – 10, 2024

All Times are Eastern Time (ET).

Tuesday, May 7, 2024
8:45–9:00 am Remote Learning Technology Session
9:00–10:00 am Panch, Mattie Intro to AI
10:00–10:15 am Break
10:15–11:15 am Jouni, Karthikesalingam Medical AI
11:15–11:30 am Break
11:30 am–12:30 pm Mattie, Panch, Mauro AI Lab - Optimizing Large Language Models
12:30–1:00 pm Mattie, Panch Q&A
Wednesday, May 8, 2024
9:00–10:00 am AI and Life Sciences
10:00–10:15 am Break
10:15–11:15 am Romero-Brufau Implementing AI in Healthcare Organizations
11:15–11:30 am Break
11:30 am–12:30 pm Mattie, Panch, Mauro AI Lab - Prompt Engineering
12:30–1:00 pm Mattie, Panch Q&A
Thursday, May 9, 2024
9:00–10:00 am Leading Digital Transformation in Healthcare Organizations
10:00–10:15 am Break
10:15–11:15 am Romero-Brufau, Lindemer Evaluating and Scaling AI in Healthcare
11:15–11:30 am Break
11:30 am–12:30 pm Mattie, Panch, Mauro AI Lab - Tuning Large Language Models
12:30–1:00 pm Panch, Mattie Q&A
Friday, May 10, 2024
9:00–10:00 am Agrawal Innovating with AI
10:00–10:15 am Break
10:15–11:15 am Brownstein, Panch AI and Intrapreneurship
11:15–11:30 am Break
11:30 am–12:30 pm Mattie, Panch, Mauro AI Lab - Developing High Performance AI
12:30–1:00 pm Mattie, Panch Q&A

This agenda is subject to change.

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Who Should Participate

This online program is designed for senior managers and executives who are responsible for developing and implementing AI strategy in their organizations and are looking to understand AI and both its current state and future.  

Participants will come from a range of organizational functions including health care delivery, health care technology, primary care systems, payers, and governments. Some titles represented in the program will include: 

  • Chief Executive Officer 
  • Chief Information Officer 
  • Chief Innovation Officer 
  • Chief Medical Informatics Officer 
  • Chief Medical Officer 
  • Clinician 
  • Data Scientist 
  • Director 
  • Engineer 
  • Innovation Specialist 
  • Finance Professional 
  • Product Manager 
  • Project Manager 
  • Venture Capital Investor