Journal Article DKFZ-2026-00259

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png
Künstliche Intelligenz in chirurgischen Disziplinen: Einsatz, Nutzen und Potenzial – ein Delphi-Expertenkonsensus.

 ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;

2026
Springer Medizin New York]

Die Urologie nn, nn () [10.1007/s00120-026-02778-8]
 GO

Abstract: 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.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.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.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.

Keyword(s): Artificial intelligence ; Delphi consensus conference ; Digitalization ; Legal framework ; Surgery

Classification:

Note: epub

Contributing Institute(s):
  1. NWG KKE Multiparametrische Methoden zur Früherkennung des Prostatakarzinoms (E250)
Research Program(s):
  1. 315 - Bildgebung und Radioonkologie (POF4-315) (POF4-315)

Appears in the scientific report 2026
Database coverage:
Medline ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; DEAL Springer ; DEAL Springer ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
Click to display QR Code for this record

The record appears in these collections:
Document types > Articles > Journal Article
Public records
Publications database

 Record created 2026-02-02, last modified 2026-02-02



Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)