Over the past decade, many new cancer treatments have been developed and made
available to patients. However, in most cases, these treatments only benefit a specific …

Aims Artificial intelligence (AI) provides a powerful tool to extract information from digitised
histopathology whole slide images. During the last 5 years, academic and commercial …

In recent years, the application of advanced analytics, especially artificial intelligence (AI), to
digital H&E images, and other histological image types, has begun to radically change how …

Clinical workflows in oncology depend on predictive and prognostic biomarkers. However,
the growing number of complex biomarkers contributes to costly and delayed decision …

Background The objective of this comprehensive pan-cancer study is to evaluate the
potential of deep learning (DL) for molecular profiling of multi-omic biomarkers directly from …

Recently, a wide spectrum of artificial intelligence (AI)–based applications in the broader
categories of digital pathology, biomarker development, and treatment have been explored …

Complete pathological response (pCR) to neoadjuvant chemotherapy (NAC) is a prognostic
factor for breast cancer (BC) patients and is correlated with improved survival. However …

Traditional pathology approaches have played an integral role in the delivery of diagnosis,
semi-quantitative or qualitative assessment of protein expression, and classification of …

Clinical efforts on precision medicine are driving the need for accurate diagnostic, new
prognostic and novel drug predictive assays to inform patient selection and stratification for …

Molecular and genomic properties are critical in selecting cancer treatments to target
individual tumors, particularly for immunotherapy. However, the methods to assess such …