Five critical quality criteria for artificial intelligence-based prediction models
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Publication date
2023-12-07
Authors
van Royen, Florien
Asselbergs, Folkert W
Alfonso, Fernando
Vardas, Panos
van Smeden, Maarten
Editors
Advisors
Supervisors
Document Type
Article
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cc_by_nc
Abstract
To raise the quality of clinical artificial intelligence (AI) prediction modelling studies in the cardiovascular health domain and thereby improve their impact and relevancy, the editors for digital health, innovation, and quality standards of the European Heart Journal propose five minimal quality criteria for AI-based prediction model development and validation studies: complete reporting, carefully defined intended use of the model, rigorous validation, large enough sample size, and openness of code and software.
Keywords
Artificial intelligence, Diagnosis, Digital health, Prediction, Prognosis, Cardiology and Cardiovascular Medicine
Citation
Van Royen, F S, Asselbergs, F W, Alfonso, F, Vardas, P & Van Smeden, M 2023, 'Five critical quality criteria for artificial intelligence-based prediction models', European heart journal, vol. 44, no. 46, pp. 4831-4834. https://doi.org/10.1093/eurheartj/ehad727