14 citations · 18 across the 3 of their papers we have counts for
3 papers
Machine learning algorithms to predict the risk of rupture of intracranial aneurysms: a systematic review
Karan Daga, Siddharth Agarwal, Zaeem Moti +5
Purpose: Subarachnoid haemorrhage is a potentially fatal consequence of intracranial aneurysm rupture, however, it is difficult to predict if aneurysms will rupture. Prophylactic t…
A self-supervised text-vision framework for automated brain abnormality detection
David A. Wood, Emily Guilhem, Sina Kafiabadi +13
Artificial neural networks trained on large, expert-labelled datasets are considered state-of-the-art for a range of medical image recognition tasks. However, categorically labelle…
Artificial intelligence for abnormality detection in high volume neuroimaging: a systematic review and meta-analysis
Siddharth Agarwal, David A. Wood, Mariusz Grzeda +5
Purpose: Most studies evaluating artificial intelligence (AI) models that detect abnormalities in neuroimaging are either tested on unrepresentative patient cohorts or are insuffic…