Keele University
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
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 · 737 Zit.
The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions
Keng‐Boon Ooi, Garry Wei‐Han Tan, Mostafa Al‐Emran et al.
2023 · 598 Zit.
Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review
Constanza L. Andaur Navarro, Johanna AAG Damen, Toshihiko Takada et al.
2021 · 332 Zit.
Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications
Farah Magrabi, Elske Ammenwerth, Jytte Brender McNair et al.
2019 · 317 Zit.
Artificial Intelligence -based technologies in nursing: A scoping literature review of the evidence
Hanna von Gerich, Hans Moen, Lorraine J. Block et al.
2021 · 268 Zit.
Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review
Paula Dhiman, Jie Ma, Constanza L. Andaur Navarro et al.
2022 · 125 Zit.
Individual Participant Data (IPD) Meta-analyses of Diagnostic and Prognostic Modeling Studies: Guidance on Their Use
Thomas P. A. Debray, Richard D Riley, Maroeska M. Rovers et al.
2015 · 124 Zit.
Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review
Constanza L. Andaur Navarro, Johanna AAG Damen, Toshihiko Takada et al.
2022 · 119 Zit.
Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved
Paula Dhiman, Jie Ma, Constanza L. Andaur Navarro et al.
2021 · 106 Zit.
Generative AI and the Automating of Academia
Richard Watermeyer, Lawrie Phipps, Donna Lanclos et al.
2023 · 102 Zit.
Methodology over metrics: current scientific standards are a disservice to patients and society
Ben Van Calster, Laure Wynants, Richard D Riley et al.
2021 · 100 Zit.
Basic principles and recommendations in clinical and field science research: 2018 update
Johnny Padulo, Francesco Oliva, Antonio Frizziero et al.
2019 · 97 Zit.
Applications of artificial intelligence and machine learning in heart failure
Tauben Averbuch, Kristen Sullivan, Andrew J. Sauer et al.
2022 · 93 Zit.
Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models
Constanza L. Andaur Navarro, Johanna AAG Damen, Maarten van Smeden et al.
2022 · 89 Zit.
Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques
Constanza L. Andaur Navarro, Johanna AAG Damen, Toshihiko Takada et al.
2020 · 84 Zit.