Would doctors dream of electric blood bankers? Large language model-based artificial intelligence performs well in many aspects of transfusion medicine

CME Editor: Julie Katz Karp, MD

Article Title: Would doctors dream of electric blood bankers? Large language model-based artificial intelligence performs well in many aspects of transfusion medicine

If you wish to receive credit for this activity, please refer to the website: https://www.wileyhealthlearning.com/trf

Educational Objective: Explore how large language model-based artificial intelligence performs on transfusion medicine tasks

Activity Disclosures 

No commercial support has been accepted related to the development or publication of this activity. CME Editor, Julie Katz Karp MD reported no conflicts of interest or financial relationships relevant to this article. This activity underwent peer review in line with the standards of editorial integrity and publication ethics. Conflicts of interest have been identified and resolved in accordance with John Wiley and Sons, Inc.’s Policy on Activity Disclosure and Conflict of Interest.

Accreditation
John Wiley & Sons, Inc. is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians and approved by the American Board of Pathology (ABPath) for Continuing Certification (CC) formerly MOC.

John Wiley and Sons, Inc. designates this journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should only claim credit commensurate with the extent of their participation in the activity. For information on applicability and acceptance of continuing medical education credit for this activity, please consult your professional licensing board.

This activity is designed to be completed within 1 hour. To successfully earn credit, participants must access the activity on https://www.wileyhealthlearning.com/trf and complete the activity during the valid credit period, which is up to three years from initial publication. Additionally, up to 3 attempts and a score of 70% or better is needed to pass the post test and claim CC credit. [ACGME competency/CC category: Medical Knowledge].