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Published on: May 20, 2018
[Validation of artificial intelligence algorithms for the surgical practice]
1Abteilung Intelligente Medizinische Systeme und Helmholtz Imaging, Deutsches Krebsforschungszentrum (DKFZ) Heidelberg, Im Neuenheimer Feld 223, 69120, Heidelberg, Deutschland. a.reinke@dkfz-heidelberg.de.
Background:
Artificial intelligence (AI) is increasingly being used in surgery; however, the validation of such systems is often methodologically insufficient.
Objective:
Which validation issues arise in surgical AI and what requirements can be derived for clinically meaningful validation strategies?
Methods:
Metric-related pitfalls reported in the literature were analyzed, combined with insights from the interdisciplinary consensus process "metrics reloaded" and its ongoing extension to surgical applications.
Results:
Recurring weaknesses are observed at the levels of data, metrics and reporting. The lack of consideration of temporal structures and aggregation in video data is particularly critical.
Discussion:
A structured, clinically grounded validation is essential for the safe use of surgical AI. The metrics reloaded procedure is currently being adapted to address surgery-specific requirements.
