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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer

The tumor suppressor TP53 is frequently mutated in hormone receptor-negative, HER2-positive breast cancer (BC), contributing to tumor aggressiveness. Traditional ancillary methods like immunohistochemistry (IHC) to assess TP53 functionality face pre- and post-analytical challenges. This proof-of-con...

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Principais autores: Chiara Frascarelli, Konstantinos Venetis, Antonio Marra, Eltjona Mane, Mariia Ivanova, Giulia Cursano, Francesca Maria Porta, Alberto Concardi, Arnaud Gerard Michel Ceol, Annarosa Farina, Carmen Criscitiello, Giuseppe Curigliano, Elena Guerini-Rocco, Nicola Fusco
Format: Artigo
Sprog:Inglês
Udgivet: Elsevier 2024-12-01
Serier:Computational and Structural Biotechnology Journal
Fag:
Breast cancer
Artificial intelligence
Deep learning
TP53
Online adgang:http://www.sciencedirect.com/science/article/pii/S2001037024004057
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