DGCyTOF: Deep learning with graphic cluster visualization to predict cell types of single cell mass cytometry data.

Cheng, Lijun; Karkhanis, Pratik; Gokbag, Birkan; Liu, Yueze; Li, Lang

Cheng, Lijun; Karkhanis, Pratik; Gokbag, Birkan; Liu, Yueze; Li, Lang.

Afiliación

Cheng L; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America.
Karkhanis P; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America.
Gokbag B; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America.
Liu Y; The Grainger College of Engineering, The University of Illinois Urbana-Champaign, Urbana and Champaign, Champaign, Illinois, United States of America.
Li L; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America.

PLoS Comput Biol ; 18(4): e1008885, 2022 04.

Article en En | MEDLINE | ID: mdl-35404970

Asunto(s)

Aprendizaje Profundo; Algoritmos; Calibración; Análisis por Conglomerados; Análisis de Componente Principal

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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