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Multiplex computational pathology for treatment response predication
Cancer Cell ( IF 48.8 ) Pub Date : 2021-08-09 , DOI: 10.1016/j.ccell.2021.07.014 Ming Y Lu 1 , Houssein A Sater 2 , Faisal Mahmood 1
中文翻译:
用于治疗反应预测的多重计算病理学
更新日期:2021-08-09
Cancer Cell ( IF 48.8 ) Pub Date : 2021-08-09 , DOI: 10.1016/j.ccell.2021.07.014 Ming Y Lu 1 , Houssein A Sater 2 , Faisal Mahmood 1
Affiliation
Recently published in Science, AstroPath outlines a standardized workflow for multiplex immunofluorescence (mIF) panel development, imaging, and analysis; showcases its potential in biomarker discovery for predicting response to anti–PD-1 treatment; and paves the way for large-scale computational pathology studies on high-quality mIF datasets using data-driven machine-learning techniques.
中文翻译:
用于治疗反应预测的多重计算病理学
最近发表在Science 上的AstroPath 概述了多重免疫荧光 (mIF) 面板开发、成像和分析的标准化工作流程;展示其在生物标志物发现中预测抗 PD-1 治疗反应的潜力;并为使用数据驱动的机器学习技术对高质量 mIF 数据集进行大规模计算病理学研究铺平了道路。