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New interpretable machine-learning method for single-cell data reveals correlates of clinical response to cancer immunotherapy.
Greene, Evan; Finak, Greg; D'Amico, Leonard A; Bhardwaj, Nina; Church, Candice D; Morishima, Chihiro; Ramchurren, Nirasha; Taube, Janis M; Nghiem, Paul T; Cheever, Martin A; Fling, Steven P; Gottardo, Raphael.
Afiliação
  • Greene E; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Finak G; Biostatistics Bioinformatics and Epidemiology Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • D'Amico LA; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Bhardwaj N; Biostatistics Bioinformatics and Epidemiology Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Church CD; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Morishima C; Cancer Immunotherapy Trials Network, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Ramchurren N; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai New York, NY, USA.
  • Taube JM; Division of Dermatology, Department of Medicine University of Washington, Seattle, WA, USA.
  • Nghiem PT; Division of Dermatology, Department of Medicine University of Washington, Seattle, WA, USA.
  • Cheever MA; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Fling SP; Cancer Immunotherapy Trials Network, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Gottardo R; Bloomberg Kimmel Institute for Cancer Immunotherapy and the Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Patterns (N Y) ; 2(12): 100372, 2021 Dec 10.
Article em En | MEDLINE | ID: mdl-34950900
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article