William Harvey Research Institute

A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME

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

2024 · 559 Zit.

Clinical applications of machine learning algorithms: beyond the black box

David Watson, Jenny Krutzinna, Ian N Bruce et al.

2019 · 435 Zit.

Artificial intelligence in cardiology: Hope for the future and power for the present

Loucia Karatzia, Nay Aung, Dunja Aksentijević

2022 · 120 Zit.

Explainable Artificial Intelligence and Cardiac Imaging: Toward More Interpretable Models

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

2023 · 91 Zit.

The Promise of AI in Detection, Diagnosis, and Epidemiology for Combating COVID-19: Beyond the Hype

Musa Abdulkareem, Steffen E. Petersen

2021 · 74 Zit.

Clinical Trial Design Principles and Outcomes Definitions for Device-Based Therapies for Hypertension: A Consensus Document From the Hypertension Academic Research Consortium

David E. Kandzari, Felix Mahfoud, Michael A. Weber et al.

2022 · 72 Zit.

Artificial Intelligence Will Transform Cardiac Imaging—Opportunities and Challenges

Steffen E. Petersen, Musa Abdulkareem, Tim Leiner

2019 · 67 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.

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.

Investigating Explainable Artificial Intelligence for MRI-based Classification of Dementia: a New Stability Criterion for Explainable Methods

Ahmed Salih, Ilaria Boscolo Galazzo, Federica Cruciani et al.

2022 · 19 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.

Artificial intelligence in paediatric endocrinology: conflict or cooperation

Paul Dimitri, Martin O. Savage

2024 · 14 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.