医学
数字化病理学
结直肠癌
放化疗
活检
新辅助治疗
数字图像分析
放射科
内科学
癌症
病理
计算机科学
乳腺癌
计算机视觉
作者
Fang Zhang,Su Yao,Zhi Li,Changhong Liang,Ke Zhao,Yanqi Huang,Ying Gao,Jinrong Qu,Zhenhui Li,Zaiyi Liu
摘要
Quantitative features extracted from biopsy digital pathology images can provide predictive information for neoadjuvant chemoradiotherapy (nCRT) in local advanced rectal cancer (LARC) Machine learning technologies are applied to build the digital-pathology-based pathology signature The pathology signature is an independent predictor of treatment response to nCRT in LARC
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