Integrating machine learning algorithms to systematically assess reactive oxygen species levels to aid prognosis and novel treatments for triple -negative breast cancer patients

Integrating machine learning algorithms to systematically assess reactive oxygen species levels to aid prognosis and novel treatments for triple -negative breast cancer patients

IntroductionBreast cancer has become one of the top health concerns for women, and triple-negative breast cancer (TNBC) leads to treatment resistance and poor prognosis due to its high degree of heterogeneity and malignancy. Reactive oxygen species (ROS) have been found to play a dual role in tumors...

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Bibliographic Details
Main Authors: Juan Li, Yu Liang, Xiaochen Zhao, Chihua Wu
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-06-01
Series:Frontiers in Immunology
Subjects:
triple negative breast cancer (TNBC)
reactive oxygen species (ROS)
machine-learning
chemotherapy
immunotherapy
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2023.1196054/full

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