Five critical quality criteria for artificial intelligence-based prediction models
Florien S van Royen, Folkert W. Asselbergs, Fernándo Alfonso, Panos Vardas, Maarten van Smeden
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.
Topics & Concepts
MedicineQuality (philosophy)Predictive modellingQuality assuranceArtificial intelligenceSoftwareMachine learningData miningComputer sciencePathologyProgramming languageEpistemologyPhilosophyExternal quality assessmentArtificial Intelligence in Healthcare and EducationMachine Learning in HealthcareRadiomics and Machine Learning in Medical Imaging