March 11, 2021 AI4C: How to Connect an Artificial Intelligence Tool to PACS

March 11, 2021


In this virtual presentation, we will show how to use Digital Imaging and Communications in Medicine (DICOM) Query and Retrieve functions to pull a study from a cloud or public picture archiving and communication system (PACS), run an artificial intelligence (AI) algorithm on those images, and store the results back to another (cloud) PACS. This is a practical example of how to both get images needed by an AI tool for inference and how to store the results back using DICOM methods. In addition, some real-world considerations are exploited, like limitations and possible issues.

Target Audience

This lecture series in intended for Physicians of all specialties, nurses, Physician Assistants, Information Technology Specialists, and Researchers interested in Artificial Intelligence in healthcare. Faculty of all levels, students, residents, and fellows welcome. Personnel from the healthcare technology sector may also be interested in attending the series.

Learning Objectives

Upon completion of this activity, participants will be able to:

  1. Describe Artificial Intelligence (AI) and Machine Learning (ML) at a high-level.
  2. Identify current limitations of AI in healthcare.
  3. Cite examples of AI as applied to imaging and other healthcare data.
  4. Describe example AI tools that can impact workflow in the healthcare arena.
  5. Utilize clinical AI applications appropriately.

Additional Information

Provided by: 

Massachusetts General Hospital and Brigham & Women's Hospital, Center for Clinical Data Science & Mass General Brigham


Course summary
Available credit: 
  • 1.00 AMA PRA Category 1 Credit™
  • 1.00 Participation
Course opens: 
Course expires: 
Event starts: 
03/11/2021 - 12:00pm EST
Event ends: 
03/11/2021 - 1:00pm EST
MGH & BWH Center for Clinical Data Science
Boston, MA
United States

Course Director

Katherine P. Andriole, PhD., FSIIM

Director of Research, Strategy and Operations
MGH & BWH Center for Clinical Data Science
Associate Professor of Radiology
Brigham and Women’s Hospital
Harvard Medical School
Boston, MA



Felipe Campos Kitamura, MD, MSc, PhD

Neuroradiologist at Federal University of Sao Paulo (UNIFESP) World University, Brazil
Deputy Editor InTraining in Radiology
Co-chair of the Machine Learning Education Subcommittee at SIIM
Member of the Machine Learning Challenge Task Force at RSNA.
Kaggle Competitions Master.

Mass General Brigham is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

Mass General Brigham designates this live activity for a maximum of 1 AMA PRA Category 1 Credit™ per session. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Available Credit

  • 1.00 AMA PRA Category 1 Credit™
  • 1.00 Participation


Please login or register to take this course.
Registration TypeTuition Fee
(per session if you are seeking credit)
MDs, DOs, NPs, & PAs$20
Other Health Care Professionals $10


Contact if you require assistance in cancelling your online registration.