Künstliche Intelligenz in chirurgischen Disziplinen: Einsatz, Nutzen und Potenzial – ein Delphi-Expertenkonsensus

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Authors: G. Duwe, Kerstin Moench, Verena Kauth, Miriam Angeloni, Jennifer Eckhoff, Magdalena Görtz, S. Hoefert, T. D. Kocar, Lisa Kollitsch, Sherif Mehralivand, D. Mercier, J. Rudolph
+7 more Johannes Rueckel, R. Schönhof, Marcus Sondermann, CAJ von Klot, A. Zamzow, J. P. Struck, Hendrik Borgmann
Cited by: 1
References: 81

Abstract

BACKGROUND: Artificial intelligence (AI) in surgical disciplines has the potential to support all areas of patient care, with the goal of improving treatment quality and patient safety. A group of multidisciplinary experts discussed the current situation as well as steps required to successfully integrate AI into surgical disciplines in the context of a consensus conference at the second Digital Health Summit (Brandenburg an der Havel, Germany) in August 2024. METHODS: A modified Delphi procedure was performed with 16 multidisciplinary physicians and scientists on the topic of AI in surgical disciplines and beyond. In two online meetings with subsequent Delphi survey rounds (LimeSurvey) and a final hybrid meeting, individual statements were contributed, discussed, and consented by all 16 participants based on current national clinical guidelines. RESULTS: From a total of 103 submitted statements, 36 statements on reality (n = 12), utopia (n = 13), and opportunities for digital transformation (n = 11) were consented after discussion and modification. We achieved a consensus of at least 75% for all the statements presented, with six of the statements achieving a strong consensus of 100% agreement. CONCLUSION: The consensus statements show the great potential of AI for improving patient care in surgical disciplines. Challenges such as the lack of digitalization structures and legal frameworks were identified, and practice-oriented proposals for implementation were developed. The need for multidisciplinary cooperation between medical professionals, politics, and industry was emphasized in order to facilitate the German healthcare system remaining competitive for the future, both nationally and internationally.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Delphi Technique in Research Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
Die Urologie
Publisher
Springer Science and Business Media LLC
Volume
65
Issue
6
Pages
627–638
Publication date
30 January 2026
Language
DE