AI Webinar Series – Webinar 4 SAM: How Machine Learning Will Change Clinical Radiology and Nuclear Medicine

MOC Part II SAM Modules

AI Webinar Series – Webinar 4:  How Machine Learning Will Change Clinical Radiology and Nuclear Medicine

Release Date: 4/28/2020
Expiration Date: 4/30/2023

SNMMI/ACNM Members: $0
Non-Members: $49.00


Continuing Education Credit Information


ABNM SAM Credit
The American Board of Nuclear Medicine has reviewed and approved this Journal SAM activity submitted by the SNMMI. This activity fulfills the requirements of the ABNM Maintenance of Certification program for self-assessment. 1.0 SAMs have been awarded for this activity.

AMA-PRA (Physician)
The Society for Nuclear Medicine and Medical Imaging, Inc. (SNMMI) is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. SNMMI designates this enduring material for a maximum of 1.0 AMA PRA Category 1 CreditsTM. Physicians should claim only credit commensurate with the extent of their participation in the activity.
Objectives

At the completion of this webinar series, the participant will be able to:
1. Examine the field of AI in current non-medical and medical applications
2. Assess the field of deep learning as an important and emerging subset of the field of AI
3. Discuss motivations for extraction of patterns of heterogeneity in uptake of radiopharmaceuticals
4. Recognize existing AI applications in industry software
5. List and understand the multiple pitfalls and challenges in AI applications
6. Become the expert on how (and how much) AI has the potential to contribute towards increasing precision medicine

Target Audience

The Life Long Learning and Self-Assessment activity is designed for all nuclear medicine physicians and radiologists.

Presenter
Greg Zaharchuk, MD, PhD

Financial Disclosure



In accordance with ACCME Revised Standards for Commercial Support and SNMMI Conflict-of-Interest Policy, the speaker has indicated no relevant relationships that could be perceived as a real or apparent conflict of interest. Disclosure of a relationship is not intended to suggest or to condone bias but is made to provide participants with information that might be of potential importance to their evaluation of the activity.


Contact Information

For questions please contact Lisa Dickinson, Associate Director of Education at ldickinson@snmmi.org or 703-652-6783.