Journal Article (Review Article)

DKFZ-2025-01457

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Validation of artificial intelligence algorithms for the surgical practice. [Validierung von künstliche Intelligenz-Algorithmen für die chirurgische Praxis.]

Reinke, A. (Last author)DKFZ*

2025
Springer Medizin Verlag GmbH [Berlin]

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Please use a persistent id in citations: doi:10.1007/s00104-025-02348-2

Abstract: Artificial intelligence (AI) is increasingly being used in surgery; however, the validation of such systems is often methodologically insufficient.Which validation issues arise in surgical AI and what requirements can be derived for clinically meaningful validation strategies?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.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.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.

Keyword(s): Assessment methods ; Metrics ; Metrics reloaded ; Surgical video analysis ; Video data

Note: #LA:E130# / epub

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Contributing Institute(s):

1. E130 Intelligente Medizinische Systeme (E130)

Research Program(s):

1. 315 - Bildgebung und Radioonkologie (POF4-315) (POF4-315)

Appears in the scientific report 2025

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Database coverage:
; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; DEAL Springer ; DEAL Springer ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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