Assessment of breast composition in MRI using artificial intelligence - A systematic review.

Introduction: Magnetic Resonance Imaging (MRI) performs a critical role in breast cancer diagnosis, especially for high-risk populations e.g. family history.

Estimating neutralising antibody responses against emerging SARS-CoV-2 variants utilising convalescent sera before the roll-out of XBB-lineage vaccines.

Background: SARS-CoV-2 immune escape variants can alter existing vaccine effectiveness. In September 2023, we aimed to predict the neutralising response against BA.2.

R-AI-diographers: a European survey on perceived impact of AI on professional identity, careers, and radiographers' roles.

Objectives: Radiographers use advanced medical imaging and radiotherapy (MIRT) equipment. They are also a digitally mature and digitally resilient workforce in healthcare. Artificial intelligence is already changing their clinical practice and roles in data acquisition, post-processing, and workflow management.

The use of artificial intelligence to aid the diagnosis of lung cancer - A retrospective-cohort study.

Introduction: AI software in the form of deep learning-based automatic detection (DLAD) algorithms for chest X-ray (CXR) interpretation have shown success in early detection of lung cancer (LC), however, there remains uncertainty related to clinical validation.

Methods: CXRs and their corresponding chest-CT scans were retrospectively collated from a single institution between January 2019-2020. A commercially available AI software was used to evaluate 320 CXRs (<6 years prior-to-diagnosis) from 105 positive LC patients and 103 negative controls.