Genehmigungspolitiken für Änderungen an maschinenlernbasierter Software als medizinisches Gerät: Eine Studie über bio-creep.

Zusammenfassung

Successful deployment of machine learning algorithms in healthcare requires careful assessments of their performance and safety. To date, the FDA approves locked algorithms prior to marketing and requires future updates to undergo separate premarket reviews. However, this negates a key feature of machine learning-the ability to learn from a growing dataset and improve over time. This paper frames the design of an approval policy, which we refer to as an automatic algorithmic change protocol (aAC