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Editorial
. 2023 May 25;50(3):161-162.
doi: 10.1159/000530978. eCollection 2023 Jun.

Omics and Machine Learning in Transfusion Medicine

Angelo D'Alessandro  1 , Peter Bugert  2
Affiliations
Editorial

Omics and Machine Learning in Transfusion Medicine

Angelo D'Alessandro et al. Transfus Med Hemother. .
No abstract available

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Conflict of interest statement

The authors have no conflicts of interest to declare.

References

    1. D’Alessandro A. Red blood cell omics and machine learning in transfusion medicine: singularity is near. Transfus Med Hemother. 2023;50. DOI: 10.1159/000529744. - DOI - PMC - PubMed
    1. Lopes MGM, Recktenwalda SM, Simionato G, Eichler H, Wagner C, Quint S, et al. Big data in transfusion medicine and artificial intelligence analysis for red blood cell quality control. Transfus Med Hemother. 2023;50. DOI: 10.1159/000530458. - DOI - PMC - PubMed
    1. Thun GA, Gueuninga M, Mattle-Greminger MP. Long-read sequencing in blood group genetics. Transfus Med Hemother. 2023;50. DOI: 10.1159/000530652. - DOI
    1. Miglio A, Cremonini V, Leonardi L, Manuali E, Coliolo P, Barbato O, et al. Omics technologies in veterinary medicine: literature review and perspectives in transfusion medicine. Transfus Med Hemother. 2023;50. DOI: 10.1159/000530870. - DOI - PMC - PubMed

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