City, University of London

Prediction of outcome in critically ill patients using artificial neural network synthesised by genetic algorithm

Richard Dybowski, Vanya Gant, Peter Weller et al.

1996 · 244 Zit.

Automation bias: Empirical results assessing influencing factors

Kate Goddard, Abdul Roudsari, Jeremy C Wyatt

2014 · 142 Zit.

Professionals’ responses to the introduction of AI innovations in radiology and their implications for future adoption: a qualitative study

Yaru Chen, Charitini Stavropoulou, Radhika Narasinkan et al.

2021 · 82 Zit.

Artificial intelligence in radiography: Where are we now and what does the future hold?

Christina Malamateniou, Karen Knapp, M. Pergola et al.

2021 · 80 Zit.

How to Discriminate between Computer-Aided and Computer-Hindered Decisions

Andrey Povyakalo, Eugenio Alberdi, Lorenzo Strigini et al.

2013 · 76 Zit.

Artificial Intelligence: Guidance for clinical imaging and therapeutic radiography professionals, a summary by the Society of Radiographers AI working group

Christina Malamateniou, Sonyia McFadden, Yasmin McQuinlan et al.

2021 · 66 Zit.

Knowledge, perceptions, and expectations of Artificial intelligence in radiography practice: A global radiography workforce survey

Theophilus N. Akudjedu, Sofia Torre, Ricardo Khine et al.

2022 · 57 Zit.

Validation framework for the use of AI in healthcare: overview of the new British standard BS30440

Mark Sujan, Cassius Smith-Frazer, Christina Malamateniou et al.

2023 · 55 Zit.

On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls

Roberto V. Zicari, James Brusseau, Stig Nikolaj Fasmer Blomberg et al.

2021 · 51 Zit.

Comparing predictions made by a prediction model, clinical score, and physicians

Ken Farion, Wojtek Michalowski, Dympna O’Sullivan et al.

2013 · 48 Zit.

Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK

Nikolaos Stogiannos, Rizwan Malik, Amrita Kumar et al.

2023 · 46 Zit.

Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study

Riaan van de Venter, Emily Skelton, Jacqueline Matthew et al.

2023 · 46 Zit.

UK reporting radiographers’ perceptions of AI in radiographic image interpretation – Current perspectives and future developments

Clare Rainey, Tracy O’Regan, Jacqueline Matthew et al.

2022 · 42 Zit.

Responsible AI practice and AI education are central to AI implementation: a rapid review for all medical imaging professionals in Europe

G. Walsh, Nikolaos Stogiannos, Riaan van de Venter et al.

2023 · 40 Zit.

The AI of the Beholder: Intra‐Professional Sensemaking of an Epistemic Technology

Harry Scarbrough, Yaru Chen, Gerardo Patriotta

2024 · 35 Zit.