De Novo Identification and Visualization of Important Cell Populations for Classic Hodgkin Lymphoma Using Flow Cytometry and Machine Learning.

Simonson, Paul D; Wu, Yue; Wu, David; Fromm, Jonathan R; Lee, Aaron Y

Simonson, Paul D; Wu, Yue; Wu, David; Fromm, Jonathan R; Lee, Aaron Y.

Afiliación

Simonson PD; Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
Wu Y; Department of Ophthalmology, University of Washington, Seattle, WA, USA.
Wu D; Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.
Fromm JR; Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.
Lee AY; Department of Ophthalmology, University of Washington, Seattle, WA, USA.

Am J Clin Pathol ; 156(6): 1092-1102, 2021 Nov 08.

Article en En | MEDLINE | ID: mdl-34175918

Asunto(s)

Citometría de Flujo; Enfermedad de Hodgkin; Aprendizaje Automático; Algoritmos; Enfermedad de Hodgkin/diagnóstico; Humanos; Redes Neurales de la Computación

Palabras clave

CNN; Convolutional neural network; Ensemble classifier; Explainability; Explainable artificial intelligence; Flow cytometry; Hodgkin lymphoma; Machine learning; Random forest; SHAP

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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Enfermedad de Hodgkin / Citometría de Flujo / Aprendizaje Automático Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Am J Clin Pathol Año: 2021 Tipo del documento: Article

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