Wellcome Trust
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
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 · 1.422 Zit.
The Hong Kong Principles for assessing researchers: Fostering research integrity
David Moher, L.M. Bouter, Sabine Kleinert et al.
2020 · 506 Zit.
Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
Baptiste Vasey, Myura Nagendran, Bruce Campbell et al.
2022 · 427 Zit.
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
Baptiste Vasey, Myura Nagendran, Bruce Campbell et al.
2022 · 294 Zit.
The value of standards for health datasets in artificial intelligence-based applications
Anmol Arora, Joseph Alderman, Joanne Palmer et al.
2023 · 235 Zit.
A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI
Viknesh Sounderajah, Hutan Ashrafian, Sherri Rose et al.
2021 · 217 Zit.
Data Sharing Under the General Data Protection Regulation
Antonia Vlahou, Dara Hallinan, Rolf Apweiler et al.
2021 · 121 Zit.
Research integrity: Don't let transparency damage science
Stephan Lewandowsky, Dorothy Bishop
2016 · 109 Zit.
Tackling bias in AI health datasets through the STANDING Together initiative
Shaswath Ganapathi, Joanne Palmer, Joseph Alderman et al.
2022 · 77 Zit.
Improving the quality of machine learning in health applications and clinical research
Bilal A. Mateen, James Liley, Alastair K. Denniston et al.
2020 · 65 Zit.
The Hong Kong Principles for Assessing Researchers: Fostering Research Integrity
David Moher, L.M. Bouter, Sabine Kleinert et al.
2019 · 56 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 · 54 Zit.
Data Management of Sensitive Human Proteomics Data: Current Practices, Recommendations, and Perspectives for the Future
Nuno Bandeira, Eric W. Deutsch, Oliver Kohlbacher et al.
2021 · 42 Zit.
Clinical trial data sharing: here’s the challenge
Sonali Kochhar, Bartha Maria Knoppers, Carrol Gamble et al.
2019 · 26 Zit.
Tackling Algorithmic Bias and Promoting Transparency in Health Datasets: The STANDING Together Consensus Recommendations
Joseph Alderman, Joanne Palmer, Elinor Laws et al.
2024 · 12 Zit.