MARATTO

article · Frontiers in Digital Health

A machine learning approach towards assessing consistency and reproducibility: an application to graft survival across three kidney transplantation eras

20243 citationsOpen accessUniversity of the Witwatersrand

Abstract

Our study emphasises the significance of analysing post-kidney transplant outcomes and identifying era-specific factors mitigating graft failure. The proposed framework can serve as a foundation for future research and assist physicians in identifying patients at risk of graft failure.

Research topics

  • Renal Transplantation Outcomes and Treatments
  • Organ Donation and Transplantation
  • Organ Transplantation Techniques and Outcomes

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.3389/fdgth.2024.1427845

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.