Machine learning outperforms traditional statistical methods in predicting kidney transplant outcomes: Turkiye multicenter cohort study.

Tabatabaei Hosseini, Seyed Amir; Dheir, Hamad; Cakir, Ulkem; Kocak, Huseyin; Celtik, Aygul; Sinangil, Ayse; Kumru, Gizem; Tuncbag, Nurcan; Turkmen, Aydin; Susal, Caner; Demir, Erol

doi:10.1097/01.tp.0001253736.71048.07

Machine learning outperforms traditional statistical methods in predicting kidney transplant outcomes: Turkiye multicenter cohort study.

Date

2026

Authors

Tabatabaei Hosseini, Seyed Amir

dc.identifier.issn

0041-1337
1534-6080

dc.identifier.doi

10.1097/01.tp.0001253736.71048.07

dc.description.volume

110

dc.description.issue

9S

Publisher

LIPPINCOTT WILLIAMS & WILKINS

DOI

10.1097/01.tp.0001253736.71048.07
10.1097/01.tp.0001253736.71048.07

Keywords

Immunology , Surgery , Transplantation

URI

https://doi.org/10.1097/01.tp.0001253736.71048.07
https://openaccess.acibadem.edu.tr/handle/11443/10569

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Machine learning outperforms traditional statistical methods in predicting kidney transplant outcomes: Turkiye multicenter cohort study.

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