March 10, 2022 AI4C: Artificial Intelligence in Medical Imaging
Technological advances in Artificial Intelligence (AI), particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in various medical fields, propelling it forward at a rapid pace. In this talk, Dr. Aerts will discuss recent developments from his group and collaborators performing research at the intersection of deep learning, radiology, oncology, cardiology, bioinformatics, and data science. Also, he will explore how these methods could impact multiple facets of medicine, with a general focus on applications in radiology, and demonstrate ways in which these methods are advancing the field. The presentation will conclude with a discussion on the need for open-source deep learning frameworks that are transparent and reproducible.
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.
Upon completion of this activity, participants will be able to:
- Describe Artificial Intelligence (AI) and Machine Learning (ML) at a high-level.
- Identify current limitations of AI in healthcare.
- Cite examples of AI as applied to imaging and other healthcare data.
- Describe example AI tools that can impact workflow in the healthcare arena.
- Utilize clinical AI applications appropriately.
Massachusetts General Hospital and Brigham & Women's Hospital, Center for Clinical Data Science & Mass General Brigham
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
Hugo Aerts, PhD
Director of the Artificial Intelligence in Medicine (AIM) Program
In support of improving patient care, Mass General Brigham is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.
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.
- 1.00 AMA PRA Category 1 Credit™
- 1.00 Participation