St Bartholomew's Hospital

A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME

Ahmed Salih, Zahra Raisi‐Estabragh, Ilaria Boscolo Galazzo et al.

2024 · 559 Zit.

Impact of the coronavirus (COVID-19) pandemic on scientific research and implications for clinical academic training – A review

Catrin Sohrabi, Ginimol Mathew, Thomas Franchi et al.

2021 · 227 Zit.

A review of evaluation approaches for explainable AI with applications in cardiology

Ahmed Salih, Ilaria Boscolo Galazzo, Polyxeni Gkontra et al.

2024 · 48 Zit.

Clinician's guide to trustworthy and responsible artificial intelligence in cardiovascular imaging

Liliána Szabó, Zahra Raisi‐Estabragh, Ahmed Salih et al.

2022 · 35 Zit.

Improving the digital health of the workforce in the COVID-19 context: an opportunity to future-proof medical training

Yang Chen, Amitava Banerjee

2020 · 34 Zit.

Large Language Models in Oncology: Revolution or Cause for Concern?

Aydin Caglayan, Wojciech Slusarczyk, Rukhshana Dina Rabbani et al.

2024 · 24 Zit.

Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation

Esther Puyol‐Antón, Bram Ruijsink, Stefan K. Piechnik et al.

2021 · 24 Zit.

PROTEUS Study: A Prospective Randomized Controlled Trial Evaluating the Use of Artificial Intelligence in Stress Echocardiography

Gary Woodward, Mamta Bajre, Sanjeev Bhattacharyya et al.

2023 · 22 Zit.

PROTEUS: A Prospective RCT Evaluating Use of AI in Stress Echocardiography

Ross Upton, Ashley P. Akerman, Thomas H. Marwick et al.

2024 · 17 Zit.

Fairness in Cardiac Magnetic Resonance Imaging: Assessing Sex and Racial Bias in Deep Learning-based Segmentation

Esther Puyol‐Antón, Bram Ruijsink, Jorge Mariscal Harana et al.

2021 · 13 Zit.

Deep learning in congenital heart disease imaging: hope but not haste

Rhodri Davies, Sonya V. Babu‐Narayan

2020 · 8 Zit.

Explainable Artificial Intelligence in Paediatric: Challenges for the Future

Ahmed Salih, Gloria Menegaz, Thillagavathie Pillay et al.

2024 · 8 Zit.

Perioperative risk scores: prediction, pitfalls, and progress

Jonathan Bedford, Oliver Redfern, Benjamin O’Brien et al.

2024 · 7 Zit.

Artificial intelligence in cardiovascular imaging: risks, mitigations and the path to safe implementation

James P. Howard, Qiang Zhang, Ahmed Salih et al.

2025 · 3 Zit.

New ways to use imaging data in cardiovascular research: survey of opinions on federated learning and synthetic data

Michelle C. Williams, Jacqueline A. L. MacArthur, Ross Forsyth et al.

2025 · 3 Zit.