University of Oslo

Low-Latency Federated Learning and Blockchain for Edge Association in Digital Twin Empowered 6G Networks

Yunlong Lu, Xiaohong Huang, Ke Zhang et al.

2020 · 476 Zit.

Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study

Miguel Areia, Yuichi Mori, Loredana Correale et al.

2022 · 214 Zit.

A systematic review of trials evaluating success factors of interventions with computerised clinical decision support

Stijn Van de Velde, Annemie Heselmans, Nicolas Delvaux et al.

2018 · 171 Zit.

The four dimensions of contestable AI diagnostics - A patient-centric approach to explainable AI

Thomas Ploug, Søren Holm

2020 · 140 Zit.

The User Experience of ChatGPT: Findings from a Questionnaire Study of Early Users

Marita Skjuve, Asbjørn Følstad, Petter Bae Brandtzæg

2023 · 128 Zit.

Artificial Intelligence Implementation in Healthcare: A Theory-Based Scoping Review of Barriers and Facilitators

Taridzo Chomutare, Miguel Tejedor, Therese Olsen Svenning et al.

2022 · 127 Zit.

Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study

Krzysztof Budzyń, Marcin Romańczyk, Diana Kitala et al.

2025 · 109 Zit.

How precision medicine and screening with big data could increase overdiagnosis

Henrik Vogt, Sara Green, Claus Thorn Ekstrøm et al.

2019 · 97 Zit.

The right to refuse diagnostics and treatment planning by artificial intelligence

Thomas Ploug, Søren Holm

2019 · 80 Zit.

Remove obstacles to sharing health data with researchers outside of the European Union

Heidi Beate Bentzen, Rosa Castro, Robin Fears et al.

2021 · 70 Zit.

The ethics of using generative AI for qualitative data analysis

Robert M. Davison, Hameed Chughtai, Petter Nielsen et al.

2024 · 70 Zit.

Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method

Omer F. Ahmad, Yuichi Mori, Masashi Misawa et al.

2020 · 67 Zit.

Incorrect results in software engineering experiments: How to improve research practices

Magne Jørgensen, Tore Dybå, Knut Liestøl et al.

2015 · 56 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.

Can I trust my fake data – A comprehensive quality assessment framework for synthetic tabular data in healthcare

Vibeke Binz Vallevik, Aleksandar Babić, Serena Marshall et al.

2024 · 49 Zit.