Artificial intelligence based surgical support for experimental laparoscopic Nissen fundoplication
This experimental study demonstrates that an AI/CV algorithm can effectively detect VQIs in digital images of Nissen fundoplications. This proof of concept does not aim to test clinical Nissen fundoplication, but provides experimental evidence that AI/CV models can be trained to classify various laparoscopic images of surgical configurations. In the future, this concept could be developed into AI based real-time surgical support to enhance surgical outcome and patient safety.
Authors
- Ciro Esposito (ORCID: https://orcid.org/0000-0002-8858-6848)
- Sameh Shehata (ORCID: https://orcid.org/0000-0003-4329-0100)
- Holger Till (ORCID: https://orcid.org/0000-0002-1350-596X)
- Dariusz Patkowski (ORCID: https://orcid.org/0000-0002-4583-5517)
- Georg Singer (ORCID: https://orcid.org/0000-0003-4770-3144)
- Tristan Till
- Chung Kwong Yeung
- Steve Rothenberg
Institutions
- Nanyang Technological University (SG)
- Medical University of Graz (AT)
- Wroclaw Medical University (PL)
- Federico II University Hospital (IT)
- Rocky Mountain Hospital for Children (US)
- Alexandria University (EG)
- University of Hong Kong (HK)
Publication Details
- Journal
- Frontiers in Pediatrics
- Published
- 2025-05-23
- DOI
- https://doi.org/10.3389/fped.2025.1584628
- Citations
- 2
- Primary Topic
- Colorectal Cancer Screening and Detection
- Type
- article
- Field-Weighted Citation Impact
- 2.09