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In this CME, Khodor Abou-Daya, MD discusses how to define machine learning and differentiate between machine learning approaches in research, describe at least two specific examples of how machine learning is currently being used in transplant research, and utilize TDA platform for exploration of high dimensional transplant patient clinical data.

Educational Objectives 

Upon completion of this activity, participants should be able to:

  • Define machine learning and differentiate between machine learning approaches in research.
  • Describe at least two specific examples of how machine learning is currently being used in transplant research.
  • Utilize TDA platform for exploration of high dimensional transplant patient clinical data.

Disclosures:

No members of the planning committee, speakers, presenters, authors, content reviewers and/or anyone else in a position to control the content of this education activity have relevant financial relationships with any companies whose primary business is producing, marketing, selling, re-selling, or distributing healthcare products used by or on patients.

Accreditation Statement

Jointly Accredited Provider Mark

In support of improving patient care, the University of Pittsburgh 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.

The University of Pittsburgh designates enduring material activity for a maximum of 0.75 AMA PRA Category 1 Credit[s]™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Other health care professionals will receive a certificate of attendance confirming the number of contact hours commensurate with the extent of participation in this activity.

For your credit transcript, please access our website 4 weeks post-completion at http://ccehs.upmc.com and follow the link to the Credit Transcript page. If you do not provide the last 5 digits of your SSN on the next page you will not be able to access a CME credit transcript. Providing your SSN is voluntary.

Release Date: 6/23/2025 | Last Modified On: 6/23/2025 | Expires: 6/23/2025

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