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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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