A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer
Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists
grade the microscopic appearance of breast tissue using the Nottingham criteria, which are …
grade the microscopic appearance of breast tissue using the Nottingham criteria, which are …
Regression-based Deep-Learning predicts molecular biomarkers from pathology slides
Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically
approved applications use this technology. Most approaches, however, predict categorical …
approved applications use this technology. Most approaches, however, predict categorical …
AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer
Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour
aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of …
aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of …
A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics
Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-
stained tumor slides for precision oncology. We present ENLIGHT–DeepPT, an indirect two …
stained tumor slides for precision oncology. We present ENLIGHT–DeepPT, an indirect two …
Protein biomarkers for subty** breast cancer and implications for future research: a 2024 update
Introduction Breast cancer subty** is used clinically for diagnosis, prognosis, and
treatment decisions. Subtypes are categorized by cell of origin, histomorphology, gene …
treatment decisions. Subtypes are categorized by cell of origin, histomorphology, gene …
Application of quantitative histomorphometric features in computational pathology
Y Shi, B Hu, M Xu, Y Yao, S Gao, X **a… - Interdisciplinary …, 2024 - Wiley Online Library
Computer vision has facilitated the execution of various computer‐aided diagnostic tasks.
From a methodological perspective, these tasks are primarily implemented using two …
From a methodological perspective, these tasks are primarily implemented using two …
Development and validation of a clinical breast cancer tool for accurate prediction of recurrence
Given high costs of Oncotype DX (ODX) testing, widely used in recurrence risk assessment
for early-stage breast cancer, studies have predicted ODX using quantitative …
for early-stage breast cancer, studies have predicted ODX using quantitative …
Multimodal histopathologic models stratify hormone receptor-positive early breast cancer
For patients with hormone receptor-positive, early breast cancer without HER2 amplification,
multigene expression assays including Oncotype DX® recurrence score (RS) have been …
multigene expression assays including Oncotype DX® recurrence score (RS) have been …
Deep learning-based risk stratification of preoperative breast biopsies using digital whole slide images
Background Nottingham histological grade (NHG) is a well established prognostic factor in
breast cancer histopathology but has a high inter-assessor variability with many tumours …
breast cancer histopathology but has a high inter-assessor variability with many tumours …
Recurrence risk stratification of hepatocellular carcinomas based on immune gene expression and features extracted from pathological images
Background Immune-based therapy is a promising type of treatment for hepatocellular
carcinoma (HCC) but has only been partially successful due to the high heterogeneity in …
carcinoma (HCC) but has only been partially successful due to the high heterogeneity in …