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Recommendations for using artificial intelligence in clinical flow cytometry.
Ng, David P; Simonson, Paul D; Tarnok, Attila; Lucas, Fabienne; Kern, Wolfgang; Rolf, Nina; Bogdanoski, Goce; Green, Cherie; Brinkman, Ryan R; Czechowska, Kamila.
Afiliação
  • Ng DP; Department of Pathology, University of Utah, Salt Lake City, Utah, USA.
  • Simonson PD; Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York, USA.
  • Tarnok A; Department of Preclinical Development and Validation, Fraunhofer Institute for Cell Therapy and Immunology, IZI, Leipzig, Germany.
  • Lucas F; Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA.
  • Kern W; MLL Munich Leukemia Laboratory GmbH, Munich, Germany.
  • Rolf N; BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.
  • Bogdanoski G; Clinical Development & Operations Quality, R&D Quality, Bristol Myers Squibb, Princeton, New Jersey, USA.
  • Green C; Translational Science, Ozette Technologies, Seattle, Washington, USA.
  • Brinkman RR; Dotmatics, Inc, Boston, Massachusetts, USA.
  • Czechowska K; Metafora Biosystems, PARIS, France.
Cytometry B Clin Cytom ; 106(4): 228-238, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38407537
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Citometria de Fluxo Limite: Humans Idioma: En Revista: Cytometry B Clin Cytom Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Citometria de Fluxo Limite: Humans Idioma: En Revista: Cytometry B Clin Cytom Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos