Neal Yuan, MD Assistant Clinical Professor of Medicine Division of Cardiology, UCSF
Disclosures: Presenter Neal Yuan MD has stated there are no relationships to disclose. Planners Jessie Holtzman MD, Elizabeth Harleman, MD and Melody Davenport-McLaughlin, BA have stated they have no relationships to disclose.
Learning Objectives:
Have a basic understanding of deep learning
Know some potential applications of deep learning in cardiology
Recognize potential challenges and pitfalls of using deep learning in clinical practice
*Views or opinions expressed in MGR are those of the speakers and do not necessarily represent the views or opinions of the organizers or the UCSF DOM.
Accreditation: The University of California, San Francisco School of Medicine (UCSF) is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.
Designation: UCSF designates this live activity for a maximum of 64 AMAPRACategory 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
The above credit is inclusive of all Fiscal year 2022/2023 SFGH Medicine Grand rounds sessions.
To claim credit for today’s Medicine Grand Rounds:
• Scan the code using your mobile device.
• Follow the link to ww2.highmarksce.com
• Enter your name and email. Select the number of credits claimed and tap Submit
• The link is active from 15 minutes after the close of the session and is open for 30 days.
Add to Calendar2023-02-21 20:00:002023-02-21 21:00:00ZSFG Medicine Grand Rounds - MGR 23028
Neal Yuan, MD
Assistant Clinical Professor of Medicine
Division of Cardiology, UCSF
Disclosures: Presenter Neal Yuan MD has stated there are no relationships to disclose. Planners Jessie Holtzman MD, Elizabeth Harleman, MD and Melody Davenport-McLaughlin, BA have stated they have no relationships to disclose.
Learning Objectives:
Have a basic understanding of deep learning
Know some potential applications of deep learning in cardiology
Recognize potential challenges and pitfalls of using deep learning in clinical practice
*Views or opinions expressed in MGR are those of the speakers and do not necessarily represent the views or opinions of the organizers or the UCSF DOM.
Accreditation: The University of California, San Francisco School of Medicine (UCSF) is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.
Designation: UCSF designates this live activity for a maximum of 64 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
The above credit is inclusive of all Fiscal year 2022/2023 SFGH Medicine Grand rounds sessions.
Zoom Information
http://tiny.ucsf.edu/DOMGrandRounds
Meeting ID: 968 1679 7792; Password: 1001
Call-in: +1 669 900 6833, +1 213 338 8477, +1 669 219 2599
To claim credit for today’s Medicine Grand Rounds:
• Scan the code using your mobile device.
• Follow the link to ww2.highmarksce.com
• Enter your name and email. Select the number of credits claimed and tap Submit
• The link is active from 15 minutes after the close of the session and is open for 30 days.
Contact Information
Melody Davenport-McLaughlin, [email protected]
This presentation will be recorded and is accessible through My Access: https://lecture.ucsf.edu/ets/Catalog/Full/ab21c2921423425398199ec7e0720d6a2
Melody Davenport-McLaughlin, [email protected]UCSF Department of Medicine at ZSFGAmerica/Los_Angelespublic
