Oncology

Researchers found that matrix assisted laser desorption ionisation imaging combined with machine learning may improve diagnosis and prognostic assessment in rare ampullary cancer.

New modelling data suggest that scaling up the global cancer workforce, especially diagnostic and surgical personnel, could substantially reduce cancer mortality worldwide by 2050.

Deep learning models accurately predicted key DCIS biomarkers from pathology slides, supporting active surveillance strategies.

A novel MRI workflow enables non invasive tumour microenvironment assessment, improving biomarker discovery and achieving strong accuracy in breast cancer validation studies.

Quantitative ultrasound combined with deep learning predicts three year survival in locally advanced breast cancer before treatment begins.

A deep learning model achieves high accuracy in brain tumour detection from MRI, improving diagnosis and reducing false positives in clinical practice.

Chromosomal instability in oesophageal adenocarcinoma promotes immunosuppression and poor outcomes, revealing new therapeutic targets in tumour immune signalling.

HBV reactivation risk increases after rituximab in lymphoma patients once antivirals stop, with most relapses occurring within the first year.