Two machine learning-derived nomogram for predicting the occurrence and severity of acute graft-versus-host disease: a retrospective study based on serum biomarkers DOI Creative Commons

Qiang He,

Xin Li, Fang Yuan

et al.

Frontiers in Genetics, Journal Year: 2024, Volume and Issue: 15

Published: Nov. 8, 2024

Acute graft-versus-host disease (aGVHD) is a common complication after allogeneic hematopoietic cell transplantation (allo-HSCT), with high morbidity and mortality. Although glucocorticoids are the standard treatment, only half of patients achieve complete remission. Thus, there an urgent need to screen biomarkers for diagnosis aGVHD assist in identification individuals at risk aGVHD. This study was construct prediction models occurrence severity using two machine learning algorithms based on serum biochemical data.

Language: Английский

Two machine learning-derived nomogram for predicting the occurrence and severity of acute graft-versus-host disease: a retrospective study based on serum biomarkers DOI Creative Commons

Qiang He,

Xin Li, Fang Yuan

et al.

Frontiers in Genetics, Journal Year: 2024, Volume and Issue: 15

Published: Nov. 8, 2024

Acute graft-versus-host disease (aGVHD) is a common complication after allogeneic hematopoietic cell transplantation (allo-HSCT), with high morbidity and mortality. Although glucocorticoids are the standard treatment, only half of patients achieve complete remission. Thus, there an urgent need to screen biomarkers for diagnosis aGVHD assist in identification individuals at risk aGVHD. This study was construct prediction models occurrence severity using two machine learning algorithms based on serum biochemical data.

Language: Английский

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