University of Oxford

The ethics of algorithms: Mapping the debate

Brent Mittelstadt, Patrick Allo, Mariarosaria Taddeo et al.

2016 · 2.653 Zit.

The future of digital health with federated learning

Nicola Rieke, Jonny Hancox, Wenqi Li et al.

2020 · 2.218 Zit.

European Union Regulations on Algorithmic Decision Making and a “Right to Explanation”

Bryce Goodman, Seth Flaxman

2017 · 1.990 Zit.

A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models

Evangelia Christodoulou, Jie Ma, Gary S. Collins et al.

2019 · 1.823 Zit.

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

Gary S. Collins, Karel G.M. Moons, Paula Dhiman et al.

2024 · 1.469 Zit.

Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies

Myura Nagendran, Yang Chen, Christopher A. Lovejoy et al.

2020 · 996 Zit.

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

Xiaoxuan Liu, Samantha Cruz Rivera, David Moher et al.

2020 · 896 Zit.

The ethics of AI in health care: A mapping review

Jessica Morley, Caio C. Vieira Machado, Christopher Burr et al.

2020 · 814 Zit.

Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence

Gary S. Collins, Paula Dhiman, Constanza L. Andaur Navarro et al.

2021 · 739 Zit.

Dynamic consent: a patient interface for twenty-first century research networks

Jane Kaye, Edgar A. Whitley, David J. Lund et al.

2014 · 720 Zit.

The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts

Brent Mittelstadt, Luciano Floridi

2015 · 681 Zit.

Artificial Intelligence and the ‘Good Society’: the US, EU, and UK approach

Corinne Cath, Sandra Wachter, Brent Mittelstadt et al.

2017 · 661 Zit.

Proceedings of the 24th International Conference on Artificial Intelligence

Qiang Yang, Michael Wooldridge

2015 · 649 Zit.

Deep learning based tissue analysis predicts outcome in colorectal cancer

Dmitrii Bychkov, Nina Linder, Riku Turkki et al.

2018 · 643 Zit.

Research Priorities for Robust and Beneficial Artificial Intelligence

Stuart Russell, Daniel Dewey, Max Tegmark

2015 · 617 Zit.