Artificial intelligence (AI) has been available in rudimentary forms for many decades. Early AI
programs were successful in niche areas such as chess or handwriting recognition …

Deep learning (DL) can accelerate the prediction of prognostic biomarkers from routine
pathology slides in colorectal cancer (CRC). However, current approaches rely on …

Pathologists worldwide are facing remarkable challenges with increasing workloads and
lack of time to provide consistently high-quality patient care. The application of artificial …

Aim Gastric cancer (GC) is a tumour entity with highly variant outcomes. Lymph node
metastasis is a prognostically adverse biomarker. We hypothesised that GC primary tissue …

Microsatellite instability (MSI) refers to alterations in the length of simple repetitive genomic
sequences. MSI status serves as a prognostic and predictive factor in colorectal cancer. The …

Abstract Programmed death-ligand 1 (PD-L1) IHC is the most commonly used biomarker for
immunotherapy response. However, quantification of PD-L1 status in pathology slides is …

Large B-cell lymphoma (LBCL) is a heterogeneous lymphoid malignancy in which MYC
gene rearrangement (MYC-R) is associated with a poor prognosis, prompting the …

Background Developing artificial intelligence (AI) models for digital pathology requires large
datasets from multiple sources. However, without careful implementation, AI models risk …

Background: Homologous Recombination Deficiency (HRD) is a pan-cancer predictive
biomarker that identifies patients who benefit from therapy with PARP inhibitors (PARPi) …

In this study, the main objective is to develop a large, pan-cancer multimodal foundation
model that can be used to predict response to neoadjuvant immunotherapy, an unmet need …