This session will focus on various aspects of Abdominal AI including how to implement AI in your practice and specific applications in GI Imaging including CT-based body composition analysis and coronary artery calcium scoring in addition to opportunistic screening. AI issues like bias, fairness, and safety will also be discussed.
Content Areas (Codes):
The following Content Areas will be printed on the certificate for this course:
- Gastrointestinal Radiology
- Informatics
Learning Objectives:
- Analyze how to implement AI in your practice.
- Describe AI for GI imaging including opportunistic screening, CT-based body composition analysis and coronary artery calcium scoring.
- Identify different aspects of AI in medical imaging including bias, fairness, and safety.
This non-CME activity is estimated to take 45 minutes to complete.
Start Date: 5/1/2025
Online Expiration Date: 4/30/2030
This educational activity was originally presented at the RSNA 2024 Annual Meeting and Scientific Assembly.
Faculty:
- Kirti Magudia, MD, PhD
- Tessa Cook, MD, PhD
- Matthew Lee, MD
- Kirti Magudia, MD, PhD
- Paul Yi, MD
Planners:
- Sergio A. Criales Vera, MD
- Soterios Gyftopoulos, MD, MBA
- Katharine Lampen-Sachar, MD
- Bertram J. Stemmler, MD
- Meike W. Vernooij, MD, PhD
- Grace G. Zhu, MD
Price:
Non-Member/Basic Member Rate: $55.00
Standard Member/Full Access Member Rate: $0.00
Refund / Exchange Policy:
RSNA will not issue any refunds or exchanges for online only versions of educational products or activities purchased online. Please review the entire product or activity description prior to purchase.
RSNA Disclaimer:
The opinions or views expressed in this activity are those of the presenters and do not necessarily reflect the opinions, recommendations or endorsement of the RSNA. Participants should critically appraise the information presented and are encouraged to consult appropriate resources for information surrounding any product or device mentioned. Information presented, as well as publications, technologies, products and/or services discussed, are intended to inform the learner about the knowledge, techniques, and experiences of RSNA faculty who are willing to share such information with colleagues. The RSNA disclaims any and all liability for damages to any individual user for all claims which may result from the use of said information, publications, technologies, products and/or services, and events.