Optimal Donor Selection for Hematopoietic Cell Transplantation Using Bayesian Machine Learning | Zendy

Brent R. Logan | Zendy; Martin Maiers | Zendy; Rodney Sparapani | Zendy; Purushottam W. Laud | Zendy; Stephen R. Spellman | Zendy; Robert E. McCulloch | Zendy; Bronwen E. Shaw | Zendy

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Optimal 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 E. 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 , credible interval , hematopoietic cell , bayesian probability , confidence interval , hematopoietic stem cell transplantation , surgery , machine learning , computer science , haematopoiesis , artificial intelligence , biology , stem cell , environmental health , genetics

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.

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