Mater Misericordiae University Hospital

The Development of Expertise in Radiology: In Chest Radiograph Interpretation, “Expert” Search Pattern May Predate “Expert” Levels of Diagnostic Accuracy for Pneumothorax Identification

Brendan S. Kelly, Louise Rainford, Sarah Darcy et al.

2016 · 139 Zit.

Identification of patient information corruption in the intensive care unit: Using a scoring tool to direct quality improvements in handover*

Brian W. Pickering, Killian Hurley, Brian Marsh

2009 · 84 Zit.

The diagnostic and prognostic value of artificial intelligence and artificial neural networks in spinal surgery

Jake McDonnell, Shane Evans, Laura McCarthy et al.

2021 · 24 Zit.

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

Brendan S. Kelly, Conor Judge, Stephanie M. Bollard et al.

2020 · 17 Zit.

Human-artificial intelligence interaction in gastrointestinal endoscopy

John Campion, Donal B O’Connor, Conor Lahiff

2024 · 16 Zit.

The AI-enhanced surgeon – integrating black-box artificial intelligence in the operating room

Ronan A. Cahill, Mindy Duffourc, Sara Gerke

2025 · 12 Zit.

Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability

Niamh Belton, Ivan Welaratne, Adil Dahlan et al.

2021 · 10 Zit.

Curriculum for safe and effective use of artificial intelligence in endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement

Yuichi Mori, Uri Kopylov, Pieter Sinonquel et al.

2025 · 5 Zit.

Systematic review of multivariable prognostic models for outcomes at least 30 days after hip fracture finds 18 mortality models but no nonmortality models warranting validation

Mary E. Walsh, Pia Kjær Kristensen, Thomas Johannesson Hjelholt et al.

2024 · 5 Zit.

Can ChatGPT and Gemini justify brain CT referrals? A comparative study with human experts and a custom prediction model

Jaka Potočnik, Edel Thomas, D Kearney et al.

2025 · 5 Zit.

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

Jaka Potočnik, Edel Thomas, Aonghus Lawlor et al.

2024 · 4 Zit.

Assessing the Quality, Readability, and Acceptability of AI-Generated Information in Plastic and Aesthetic Surgery

Muireann Keating, Stephanie M. Bollard, Shirley Potter

2024 · 3 Zit.

Cognitive vision: AI automation of the surgical eye in fluorescence angiography – correspondence

Ronan A. Cahill

2024 · 3 Zit.

Artificial Intelligence and the Future of Spine Surgery

Katharina Nagassima Rodrigues dos Reis, Shane Evans, Jake McDonnell et al.

2020 · 2 Zit.

Legal implications of AI standard of care integration on patients’ informed consent: lessons from surgery

Mindy Duffourc, Ronan A. Cahill

2025 · 1 Zit.