Emerging use of machine learning and advanced technologies to assess red cell quality.

Sebastian, Joseph A; Kolios, Michael C; Acker, Jason P

Sebastian, Joseph A; Kolios, Michael C; Acker, Jason P.

Afiliação

Sebastian JA; Institute of Biomedical Engineering, University of Toronto, 164 College St., Toronto, Ontario, M5S 3G9, Canada; Translational Biology and Engineering Program, Ted Rogers Center for Heart Research, 661 University Avenue, Toronto, ON, M5G 1X8, Canada. Electronic address: j.sebastian@mail.utoronto.ca.
Kolios MC; Department of Physics, Ryerson University, 350 Victoria St., Toronto, Ontario, M5B 2K3, Canada; Institute of Biomedical Engineering, Science and Technology (iBEST), A Partnership Between Ryerson University and St. Michael's Hospital, 209 Victoria St, Toronto, Ontario, M5B 1T8, Canada; Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, 209 Victoria St., Toronto, Ontario, M5B 1T8, Canada. Electronic address: mkolios@ryerson.ca.
Acker JP; Centre for Innovation, Canadian Blood Services, 8249-114 St., Edmonton, Alberta, T6G 2R8, Canada; Department of Laboratory Medicine and Pathology, University of Alberta, 8249-114 St., Edmonton, Alberta, T6G 2R8, Canada. Electronic address: jacker@ulberta.ca.

Transfus Apher Sci ; 59(6): 103020, 2020 Dec.

Article em En | MEDLINE | ID: mdl-33246838

Assuntos

Inteligência Artificial/normas; Eritrócitos/metabolismo; Citometria de Fluxo/métodos; Aprendizado de Máquina/normas; Humanos

Palavras-chave

Artificial intelligence; Erythrocyte; Imaging flow cytometry; Microfluidics; Neural network

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Eritrócitos / Citometria de Fluxo / Aprendizado de Máquina Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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