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

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

doi:10.1038/s41746-024-01104-w

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

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

^*Corresponding author for this work

Julius Center, dept. Epidemiology & Health Economics

Research output: Contribution to journal › Comment/Letter to the editor › Academic › peer-review

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.

Original language	English
Article number	119
Number of pages	4
Journal	NPJ DIGITAL MEDICINE
Volume	7
Issue number	1
DOIs	https://doi.org/10.1038/s41746-024-01104-w
Publication status	Published - 8 May 2024

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van Genderen, M. E., van de Sande, D., Hooft, L., Reis, A. A., Cornet, A. D., Oosterhoff, J. H. F., van der Ster, B. J. P., Huiskens, J., Townsend, R., van Bommel, J., Gommers, D., & van den Hoven, J. (2024). Charting a new course in healthcare: early-stage AI algorithm registration to enhance trust and transparency. NPJ DIGITAL MEDICINE, 7(1), Article 119. https://doi.org/10.1038/s41746-024-01104-w

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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.",

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van Genderen, ME, van de Sande, D, Hooft, L, Reis, AA, Cornet, AD, Oosterhoff, JHF, van der Ster, BJP, Huiskens, J, Townsend, R, van Bommel, J, Gommers, D & van den Hoven, J 2024, 'Charting a new course in healthcare: early-stage AI algorithm registration to enhance trust and transparency', NPJ DIGITAL MEDICINE, vol. 7, no. 1, 119. https://doi.org/10.1038/s41746-024-01104-w

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T1 - Charting a new course in healthcare

T2 - early-stage AI algorithm registration to enhance trust and transparency

AU - van Genderen, Michel E.

AU - van de Sande, Davy

AU - Hooft, Lotty

AU - Reis, Andreas Alois

AU - Cornet, Alexander D.

AU - Oosterhoff, Jacobien H.F.

AU - van der Ster, Björn J.P.

AU - Huiskens, Joost

AU - Townsend, Reggie

AU - van Bommel, Jasper

AU - Gommers, Diederik

AU - van den Hoven, Jeroen

PY - 2024/5/8

Y1 - 2024/5/8

N2 - 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.

AB - 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.

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M3 - Comment/Letter to the editor

AN - SCOPUS:85192384411

SN - 2398-6352

VL - 7

JO - NPJ DIGITAL MEDICINE

JF - NPJ DIGITAL MEDICINE

IS - 1

M1 - 119

ER -

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

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