AI in Medicine: Medical Image Interpretation

  • HMX
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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

Explore options to bundle courses and save.

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. 

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Participant Types

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 Apply

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.

Additional Course Information

For information around payments and policies, please review our frequently asked questions.

Frequently Asked Questions

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  • Automating Lung Disease Detection from Chest X-Rays
  • Results of Deep Learning for Chest X-Rays
  • Predicting Cardiovascular Risk from Retinal Images
  • Navigating Challenges in Retinal Image Analysis with Deep Learning
  • Predicting Major Adverse Cardiovascular Events
  • Enhancing Dermatologic Diagnosis with Deep Learning
  • Unpacking the Potential and Challenges of Deep Learning in Dermatologic Analysis
  • Results of Deep Learning in Dermatologic Diagnosis
  • In Practice: Evolving Applications of AI in Medical Imaging

Earn a short course certificate of completion when you finish all coursework within 8 weeks.

Are you ready to elevate your educational journey and maximize the investment in your future?

You can bundle up to five HMX short courses. Bundle discounts apply to all courses selected. All courses in a bundle must be completed during the following two enrollment periods.

Two-course bundle: 25% discount 
Three-course bundle: 30% discount 
Four-course bundle: 35% discount
Five-course bundle: 40% discount

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.

Contact Our Team

Faculty

HMX courses are led by Harvard Medical School faculty, working in collaboration with a multi-disciplinary team of experts in biomedical visualization, assessment, and the science of learning to create a unique learning experience that will stay with you.
Pranav Rajpurkar headshot.

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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