Evaluating the Role of Machine Learning in Predicting Lymphovascular Invasion in Breast Cancer Using MRI Radiomics
Machine learning with MRI radiomics offers promise for non-invasive lymphovascular invasion prediction in breast cancer, but limitations require further refinement.
Advancing Cancer Diagnostics: Evaluating the Potential of Ga-68 FAPi-46 PET Imaging in Solid Tumours
Advancing cancer diagnostics, the study evaluates Ga-68 FAPi-46 PET imaging’s potential to map FAP expression non-invasively in solid tumours.
AI-Guided Prognostic Tool for Early Detection of Dementia Using Non-Invasive Clinical Data: A Multicenter Validation Study
The study validates an AI-guided prognostic tool for early dementia detection, leveraging non-invasive clinical data, achieving generalisability across diverse, multicentre settings.
From Missed Cases to Machine Insight: Evaluating AI for Intracranial Haemorrhage Diagnosis
Discover how intracranial haemorrhage detection can be enhanced with AI: a breakthrough in emergency neuroradiology.
From Pixels to Prognosis: Evaluating AI Support for Mitral Stenosis Diagnosis
Discover the benefits of AI echocardiography mitral stenosis diagnosis, combined with advanced digital processing methods.
Optimising Neuroimaging Classification: A Critical Review of 3D-to-2D Knowledge Distillation in Deep Learning
The study critically evaluates 3D-to-2D knowledge distillation in neuroimaging classification, balancing volumetric insights with computational efficiency for real-world applications.









