Developing, implementing and governing artificial intelligence in medicine
a step-by-step approach to prevent an artificial intelligence winter
Davy van de Sande (Erasmus MC)
Michel E. Van Genderen (Erasmus MC)
J.M. Smit (Erasmus MC, TU Delft - Pattern Recognition and Bioinformatics)
Joost Huiskens (SAS Institute Inc.)
Jacob J. Visser (Student TU Delft, Erasmus MC)
Robert E.R. Veen (Erasmus MC)
Edwin Van Unen (SAS Institute Inc.)
Oliver Hilgers Ba (CE Plus GmbH)
Diederik Gommers (Erasmus MC)
Jasper van Bommel (Erasmus MC)
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Abstract
Objective Although the role of artificial intelligence (AI) in medicine is increasingly studied, most patients do not benefit because the majority of AI models remain in the testing and prototyping environment. The development and implementation trajectory of clinical AI models are complex and a structured overview is missing. We therefore propose a step-by-step overview to enhance clinicians' understanding and to promote quality of medical AI research. Methods We summarised key elements (such as current guidelines, challenges, regulatory documents and good practices) that are needed to develop and safely implement AI in medicine. Conclusion This overview complements other frameworks in a way that it is accessible to stakeholders without prior AI knowledge and as such provides a step-by-step approach incorporating all the key elements and current guidelines that are essential for implementation, and can thereby help to move AI from bytes to bedside.
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