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Machine learning-based prediction of health outcomes in pediatric organ transplantation recipients

Wednesday, May 10th, 2023, from 4:00 PM ET to 5:00 PM ET • Co-sponsored by AST's Psychosocial and Ethics Community of Practice (PSECOP) and Pediatrics Community of Practice (PCOP)

"Machine learning–based prediction of health outcomes in pediatric organ transplantation recipients"
(JAMIA Open. 2021 Mar 12;4(1):ooab008. doi: 10.1093/jamiaopen/ooab008. eCollection 2021 Jan.)

In this article:
Prediction of post-transplant health outcomes and identification of key factors remain important issues for pediatric transplant teams and researchers... The purpose of [this] study was to examine machine learning (ML) models predicting post-transplant hospitalization in a sample of pediatric kidney, liver, and heart transplant recipients from a large solid organ transplant program.

The panelists also plan to touch on broader aspects of artificial intelligence in vulnerable transplant populations as part of the discussion.

Speaker:
- Michael Killian, PhD, MSW • Florida State University College of Social Work, Tallahassee, FL

Moderator:
- Ashley Spann, MD, MS Applied Clinical Informatics • Vanderbilt University Medical Center, Nashville, TN

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