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.
© 2020 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.