Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs

Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs

Abstract The dynamic contrast-enhanced MR imaging plays a crucial role in evaluating the effectiveness of neoadjuvant chemotherapy (NAC) even since its early stage through the prediction of the final pathological complete response (pCR). In this study, we proposed a transfer learning approach to pre...

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Auteurs principaux: Maria Colomba Comes, Annarita Fanizzi, Samantha Bove, Vittorio Didonna, Sergio Diotaiuti, Daniele La Forgia, Agnese Latorre, Eugenio Martinelli, Arianna Mencattini, Annalisa Nardone, Angelo Virgilio Paradiso, Cosmo Maurizio Ressa, Pasquale Tamborra, Vito Lorusso, Raffaella Massafra
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
Medicine
R
Science
Q
Accès en ligne:https://doaj.org/article/0c54abc80b30475eb5c5e7ab5ee519b9
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https://doaj.org/article/0c54abc80b30475eb5c5e7ab5ee519b9

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