Aarhus University

The TRIPOD-LLM reporting guideline for studies using large language models

Jack Gallifant, Majid Afshar, Saleem Ameen et al.

2025 · 301 Zit.

Artificial Intelligence and Patient-Centered Decision-Making

Jens Christian Bjerring, Jacob Busch

2020 · 272 Zit.

Fighting reviewer fatigue or amplifying bias? Considerations and recommendations for use of ChatGPT and other large language models in scholarly peer review

Mohammad Hosseini, Serge P. J. M. Horbach

2023 · 200 Zit.

Embryo selection with artificial intelligence: how to evaluate and compare methods?

Mikkel Fly Kragh, Henrik Karstoft

2021 · 116 Zit.

The Digital Health Competencies in Medical Education Framework

Josip Car, Qi Chwen Ong, Tatiana Erlikh Fox et al.

2025 · 78 Zit.

The emergence of new data work occupations in healthcare: The case of medical scribes

Claus Bossen, Yunan Chen, Kathleen H. Pine

2019 · 78 Zit.

XAIR: A Framework of Explainable AI in Augmented Reality

Xuhai Xu, Anna Yu, Tanya R. Jonker et al.

2023 · 69 Zit.

A joint ESTRO and AAPM guideline for development, clinical validation and reporting of artificial intelligence models in radiation therapy

Coen Hurkmans, Jean‐Emmanuel Bibault, Kristy K. Brock et al.

2024 · 68 Zit.

Transfer learning for non-image data in clinical research: A scoping review

Andreas Ebbehøj, Mette Østergaard Thunbo, Ole Emil Andersen et al.

2022 · 66 Zit.

ChatGPT- versus human-generated answers to frequently asked questions about diabetes: A Turing test-inspired survey among employees of a Danish diabetes center

Ádám Hulmán, Ole L. Dollerup, Jesper Friis Mortensen et al.

2023 · 64 Zit.

Generative Artificial Intelligence (GenAI) in the research process – A survey of researchers’ practices and perceptions

Jens Peter Andersen, Lise Degn, Rachel Fishberg et al.

2025 · 64 Zit.

Attitude of Brazilian dentists and dental students regarding the future role of artificial intelligence in oral radiology: a multicenter survey

Ruben Pauwels, Yumi Chokyu Del Rey

2020 · 62 Zit.

Explainable AI, But Explainable to Whom? An Exploratory Case Study of xAI in Healthcare

Julie Gerlings, Millie Søndergaard Jensen, Arisa Shollo

2021 · 61 Zit.

Building truths in AI: Making predictive algorithms doable in healthcare

Anne Henriksen, Anja Bechmann

2020 · 54 Zit.

Strengthening research integrity: which topic areas should organisations focus on?

Mads P. Sørensen, Tine Ravn, Ana Marušić et al.

2021 · 52 Zit.