Predicting treatment response to neoadjuvant chemoradiotherapy in local advanced rectal cancer by biopsy digital pathology image features.

Fang ZhangSu YaoZhi LiChanghong LiangKe ZhaoYanqi HuangYing GaoJinrong QuZhen-Hui Li Zhenyu Liu

Published in: Clinical and translational medicine (2020)

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.

Keyphrases

rectal cancer
locally advanced
machine learning
deep learning
squamous cell carcinoma
ultrasound guided
radiation therapy
healthcare
lymph node
high resolution
convolutional neural network
artificial intelligence
mass spectrometry
smoking cessation
health information
big data