A machine-learning method for biobank-scale genetic prediction of blood group antigens

A key element for successful blood transfusion is compatibility of the patient and donor red blood cell (RBC) antigens. Precise antigen matching reduces the risk for immunization and other adverse transfusion outcomes. RBC antigens are encoded by specific genes, which allows developing computational...

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Veröffentlicht in:	PLoS computational biology 2024-03, Vol.20 (3), p.e1011977-e1011977
Hauptverfasser:	Hyvärinen, Kati, Haimila, Katri, Moslemi, Camous, Biobank, Blood Service, Olsson, Martin L, Ostrowski, Sisse R, Pedersen, Ole B, Erikstrup, Christian, Partanen, Jukka, Ritari, Jarmo
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Antigens Biobanks Biology and Life Sciences Blood & organ donations Blood banks Blood donors Blood groups Blood transfusion Classification Clinical Medicine Computer and Information Sciences Datasets Erythrocytes Forecasts and trends Genotype & phenotype Genotypes Genotyping Hematologi Hematology Immunization Klinisk medicin Machine learning Medical and Health Sciences Medicin och hälsovetenskap Medicine and Health Sciences Methods People and Places Prediction models Research and Analysis Methods Risk reduction Technology application Transfusion
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