Open AccessOptimal Donor Selection for Hematopoietic Cell Transplantation Using Bayesian Machine Learning
Author(s) -
Brent R. Logan,
Martin Maiers,
Rodney Sparapani,
Purushottam W. Laud,
Stephen R. Spellman,
Robert McCulloch,
Bronwen E. Shaw
Publication year - 2021
Publication title -
jco clinical cancer informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.188
H-Index - 12
ISSN - 2473-4276
DOI - 10.1200/cci.20.00185
Subject(s) - interquartile range , medicine , transplantation , selection (genetic algorithm) , population , hematopoietic cell , credible interval , hematopoietic stem cell transplantation , confidence interval , bayesian probability , surgery , machine learning , haematopoiesis , computer science , biology , artificial intelligence , stem cell , genetics , environmental health
Donor selection practices for matched unrelated donor (MUD) hematopoietic cell transplantation (HCT) vary, and the impact of optimizing donor selection in a patient-specific way using modern machine learning (ML) models has not been studied.