AI in Medicine: Medical Image Interpretation
- HMX
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Group Enrollment Option Popular with companies and institutions for team-wide training.
Learn about advances in interpretation of medical images using deep learning systems that can aid in clinical screening and diagnosis.
- Online; Self-Paced
Enroll and gain access to course materials to complete at your own pace.
$495
Save and learn more with discounted multi‑course bundles or our all‑access HMX and HealthXcelerate Learning Pass.
Certificate
Earn a short course certificate of completion when you finish all coursework within 8 weeks.
3-4 Hours
Most people can expect to complete short courses in 3-4 hours.
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Overview
Recent advances in AI have transformed the use of deep learning for interpreting medical images, such that computers can now effectively “learn from pixels”, along with other sources of clinical data, to achieve levels of diagnostic accuracy that rival (and sometimes exceed) those of human experts.
In this HMX short course, you will learn from leading experts about the key concepts and evolving impact of AI on medical image interpretation. Understanding these recent advances and the key developments that have enabled them will provide you with a strong basis for understanding future developments in this field.
Who Should Participate
Clinicians and health care professionals; researchers in biomedicine and technology sectors; and professionals in biotechnology or related health care fields
About the Program
HMX short courses feature targeted lessons on the latest medical science topics and advancements. Stay up-to-date on essential knowledge by exploring specialized topics in a shorter format designed for busy professionals.
Who Should Enroll
This course will benefit learners such as clinical professionals seeking to understand how AI can improve analysis of various types of medical images, including the advantages and limitations of these models; biomedical and medical technology researchers who are interested in using AI models to analyze medical images and would like to understand the key principles of how these models are trained; professionals in health care-related fields who are eager to understand the link between clinical challenges and AI-based solutions, and how AI could be incorporated into the next generation of medical imaging technologies.
Course Format
Most people can expect to spend 3-4 hours total on an HMX short course. In order to be considered for a short course certificate of completion, you must complete your coursework within eight weeks.
Extend Your Learning and Save More
Whether you are building your medical science knowledge, preparing for advanced study, or expanding your understanding of the health care ecosystem, combining courses helps you connect concepts across disciplines while saving on enrollment.
You can bundle up to five HMX or HealthXcelerate courses. Bundle discounts apply to all courses selected. A bundle can consist of courses in the same upcoming enrollment period or the following enrollment period.
Two-course bundle: 25% discount
Three-course bundle: 30% discount
Four-course bundle: 35% discount
Five-course bundle: 40% discount
View all bundle-eligible programs
With the HMX and HealthXcelerate Learning Pass, a $4,950 investment unlocks one year of unlimited enrollment to Harvard Medical School's portfolio of HMX and HealthXcelerate online courses, empowering you to advance your knowledge of health care and medical science in the areas that matter most to your goals. Start Learning
HMX and HealthXcelerate courses are ideal for organizations looking to train teams or larger groups. Group pricing is available, making it a cost-effective investment in team development.
Group Enrollments
HMX courses are ideal for organizations looking to train teams or larger groups. Group pricing is available, making it a cost-effective investment in team development.
Faculty
Pranav Rajpurkar
PhD
- Assistant Professor of Biomedical Informatics, Harvard Medical School
Matthew Lungren, MD, MPH
Chief Data Science Officer, Microsoft Health & Life Sciences / Clinical Associate Professor, University of California / Adjunct Professor, Stanford University
Michael Parker, MD
Assistant Professor of Medicine, Harvard Medical School, Beth Israel Deaconess Medical Center / Associate Dean for Online Learning Research, Harvard Medical School
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