Interpretable Machine Learning Models to Predict the Resistance of Breast Cancer Patients to Doxorubicin from Their microRNA Profiles.

Ogunleye, Adeolu Z; Piyawajanusorn, Chayanit; Gonçalves, Anthony; Ghislat, Ghita; Ballester, Pedro J

Ogunleye, Adeolu Z; Piyawajanusorn, Chayanit; Gonçalves, Anthony; Ghislat, Ghita; Ballester, Pedro J.

Afiliação

Ogunleye AZ; Cancer Research Center of Marseille (CRCM), INSERM U1068, Marseille, F-13009, France.
Piyawajanusorn C; Cancer Research Center of Marseille (CRCM), Institut Paoli-Calmettes, Marseille, F-13009, France.
Gonçalves A; Cancer Research Center of Marseille (CRCM), Aix-Marseille Université, Marseille, F-13284, France.
Ghislat G; Cancer Research Center of Marseille (CRCM), CNRS UMR7258, Marseille, F-13009, France.
Ballester PJ; Cancer Research Center of Marseille (CRCM), INSERM U1068, Marseille, F-13009, France.

Adv Sci (Weinh) ; 9(24): e2201501, 2022 08.

Article em En | MEDLINE | ID: mdl-35785523

Assuntos

Neoplasias da Mama; MicroRNAs; Algoritmos; Neoplasias da Mama/tratamento farmacológico; Neoplasias da Mama/genética; Doxorrubicina/uso terapêutico; Feminino; Humanos; Aprendizado de Máquina; MicroRNAs/genética

Palavras-chave

artificial intelligence; machine learning; multiomics; precision oncology; tumor profiling

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / MicroRNAs Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: Adv Sci (Weinh) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: França

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