Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

There is a need to identify biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether p...

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Hlavní autoři:	Ehsan Irajizad, Ranran Wu, Jody Vykoukal, Eunice Murage, Rachelle Spencer, Jennifer B. Dennison, Stacy Moulder, Elizabeth Ravenberg, Bora Lim, Jennifer Litton, Debu Tripathym, Vicente Valero, Senthil Damodaran, Gaiane M. Rauch, Beatriz Adrada, Rosalind Candelaria, Jason B. White, Abenaa Brewster, Banu Arun, James P. Long, Kim Anh Do, Sam Hanash, Johannes F. Fahrmann
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Frontiers Media S.A. 2022-08-01
Edice:	Frontiers in Artificial Intelligence
Témata:	triple-negative breast cancer biomarkers artificial intelligence deep-learning model neoadjuvant chemotherapy prediction
On-line přístup:	https://www.frontiersin.org/articles/10.3389/frai.2022.876100/full
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