Fei Chen

Machine learning-based quantitative pathology reveals intratumoral heterogeneity in ductal carcinoma in situ and predicts invasive upstaging.

This study aimed to develop a machine learning framework for objective ductal carcinoma in situ (DCIS) grading and to investigate intratumoral heterogeneity as a predictive biomarker. The grading framework was developed using 267 DCIS resections and validated on two external test sets (n=116 and n=69). A single-cell gr...