Predicting Response of Triple-Negative Breast Cancer to Neoadjuvant Chemotherapy Using a Deep Convolutional Neural Network-Based Artificial Intelligence Tool.

Krishnamurthy, Savitri; Jain, Parag; Tripathy, Debu; Basset, Roland; Randhawa, Ramandeep; Muhammad, Hassan; Huang, Wei; Yang, Hua; Kummar, Shivaani; Wilding, George; Roy, Rajat

Krishnamurthy, Savitri; Jain, Parag; Tripathy, Debu; Basset, Roland; Randhawa, Ramandeep; Muhammad, Hassan; Huang, Wei; Yang, Hua; Kummar, Shivaani; Wilding, George; Roy, Rajat.

Afiliação

Krishnamurthy S; University of Texas MD Anderson Cancer Center, Houston, TX.
Jain P; PathomIQ Inc, Cupertini, CA.
Tripathy D; University of Texas MD Anderson Cancer Center, Houston, TX.
Basset R; University of Texas MD Anderson Cancer Center, Houston, TX.
Randhawa R; PathomIQ Inc, Cupertini, CA.
Muhammad H; PathomIQ Inc, Cupertini, CA.
Huang W; PathomIQ Inc, Cupertini, CA.
Yang H; PathomIQ Inc, Cupertini, CA.
Kummar S; Oregon Health Science University, Portland, OR.
Wilding G; PathomIQ Inc, Cupertini, CA.
Roy R; PathomIQ Inc, Cupertini, CA.

JCO Clin Cancer Inform ; 7: e2200181, 2023 03.

Article em En | MEDLINE | ID: mdl-36961981

Assuntos

Terapia Neoadjuvante; Neoplasias de Mama Triplo Negativas; Humanos; Terapia Neoadjuvante/métodos; Neoplasias de Mama Triplo Negativas/diagnóstico; Neoplasias de Mama Triplo Negativas/tratamento farmacológico; Neoplasias de Mama Triplo Negativas/genética; Inteligência Artificial; Amarelo de Eosina-(YS)/uso terapêutico; Hematoxilina/uso terapêutico; Redes Neurais de Computação

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Terapia Neoadjuvante / Neoplasias de Mama Triplo Negativas Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: JCO Clin Cancer Inform Ano de publicação: 2023 Tipo de documento: Article

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