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Charting a new course in healthcare: early-stage AI algorithm registration to enhance trust and transparency

Charting a new course in healthcare: early-stage AI algorithm registration to enhance trust and transparency

Authors :
Michel E. van Genderen
Davy van de Sande
Lotty Hooft
Andreas Alois Reis
Alexander D. Cornet
Jacobien H. F. Oosterhoff
Björn J. P. van der Ster
Joost Huiskens
Reggie Townsend
Jasper van Bommel
Diederik Gommers
Jeroen van den Hoven
Source :
npj Digital Medicine, Vol 7, Iss 1, Pp 1-4 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

AI holds the potential to transform healthcare, promising improvements in patient care. Yet, realizing this potential is hampered by over-reliance on limited datasets and a lack of transparency in validation processes. To overcome these obstacles, we advocate the creation of a detailed registry for AI algorithms. This registry would document the development, training, and validation of AI models, ensuring scientific integrity and transparency. Additionally, it would serve as a platform for peer review and ethical oversight. By bridging the gap between scientific validation and regulatory approval, such as by the FDA, we aim to enhance the integrity and trustworthiness of AI applications in healthcare.

Details

Language :
English
ISSN :
23986352
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
npj Digital Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.3cde30344e134274be59fb84291d5dd8
Document Type :
article
Full Text :
https://doi.org/10.1038/s41746-024-01104-w