Predicting pathological complete response to neoadjuvant systemic therapy for triple-negative breast cancers using deep learning on multiparametric MRIs.

Zhou, Zijian; Adrada, Beatriz E; Candelaria, Rosalind P; Elshafeey, Nabil A; Boge, Medine; Mohamed, Rania M; Pashapoor, Sanaz; Sun, Jia; Xu, Zhan; Panthi, Bikash; Son, Jong Bum; Guirguis, Mary S; Patel, Miral M; Whitman, Gary J; Moseley, Tanya W; Scoggins, Marion E; White, Jason B; Litton, Jennifer K; Valero, Vincente; Hunt, Kelly K; Tripathy, Debu; Yang, Wei; Wei, Peng; Yam, Clinton; Pagel, Mark D; Rauch, Gaiane M; Ma, Jingfei

Zhou, Zijian; Adrada, Beatriz E; Candelaria, Rosalind P; Elshafeey, Nabil A; Boge, Medine; Mohamed, Rania M; Pashapoor, Sanaz; Sun, Jia; Xu, Zhan; Panthi, Bikash; Son, Jong Bum; Guirguis, Mary S; Patel, Miral M; Whitman, Gary J; Moseley, Tanya W; Scoggins, Marion E; White, Jason B; Litton, Jennifer K; Valero, Vincente; Hunt, Kelly K; Tripathy, Debu; Yang, Wei; Wei, Peng; Yam, Clinton; Pagel, Mark D; Rauch, Gaiane M; Ma, Jingfei.

Annu Int Conf IEEE Eng Med Biol Soc ; 2023: 1-4, 2023 07.

Article in En | MEDLINE | ID: mdl-38083160

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Triple Negative Breast Neoplasms / Deep Learning / Multiparametric Magnetic Resonance Imaging Limits: Humans Language: En Journal: Annu Int Conf IEEE Eng Med Biol Soc Year: 2023 Document type: Article

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