Aonghus Lawlor

Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE)

2022 · 227 Zit. · European Radiology

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

2024 · 68 Zit. · British Journal of Sports Medicine

Cybersecurity considerations for radiology departments involved with artificial intelligence

2023 · 24 Zit. · European Radiology

Radiology artificial intelligence, a systematic evaluation of methods (RAISE): a systematic review protocol

2020 · 17 Zit. · Insights into Imaging

Cybersecurity in Healthcare

2022 · 17 Zit. · Integrated science

The ethical matrix as a method for involving people living with disease and the wider public (PPI) in near-term artificial intelligence research

2023 · 15 Zit. · Radiography

Enterprise imaging and big data: A review from a medical physics perspective

2021 · 14 Zit. · Physica Medica

DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy

2023 · 13 Zit. · European Radiology

Automated vetting of radiology referrals: exploring natural language processing and traditional machine learning approaches

2022 · 12 Zit. · Insights into Imaging

Correction to: Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE)

2022 · 11 Zit. · European Radiology

A survey of Paediatric Radiology Artificial Intelligence

2024 · 7 Zit. · medRxiv

Can ChatGPT4-vision identify radiologic progression of multiple sclerosis on brain MRI?

2025 · 6 Zit. · European Radiology Experimental

How to apply evidence-based practice to the use of artificial intelligence in radiology (EBRAI) using the data algorithm training output (DATO) method

2023 · 5 Zit. · British Journal of Radiology

Machine learning and deep learning for classifying the justification of brain CT referrals

2024 · 4 Zit. · European Radiology

iSPAN: Explainable prediction of outcomes post thrombectomy with Machine Learning

2024 · 1 Zit. · European Journal of Radiology