Artificial intelligence and automation in endoscopy and surgery

Article


Chadebecq, F., Lovat, L. and Stoyanov, D. 2023. Artificial intelligence and automation in endoscopy and surgery. Nature Reviews Gastroenterology and Hepatology. 20 (3), pp. 171-182. https://doi.org/10.1038/s41575-022-00701-y
TypeArticle
TitleArtificial intelligence and automation in endoscopy and surgery
AuthorsChadebecq, F., Lovat, L. and Stoyanov, D.
Abstract

Modern endoscopy relies on digital technology, from high-resolution imaging sensors and displays to electronics connecting configurable illumination and actuation systems for robotic articulation. In addition to enabling more effective diagnostic and therapeutic interventions, the digitization of the procedural toolset enables video data capture of the internal human anatomy at unprecedented levels. Interventional video data encapsulate functional and structural information about a patient’s anatomy as well as events, activity and action logs about the surgical process. This detailed but difficult-to-interpret record from endoscopic procedures can be linked to preoperative and postoperative records or patient imaging information. Rapid advances in artificial intelligence, especially in supervised deep learning, can utilize data from endoscopic procedures to develop systems for assisting procedures leading to computer-assisted interventions that can enable better navigation during procedures, automation of image interpretation and robotically assisted tool manipulation. In this Perspective, we summarize state-of-the-art artificial intelligence for computer-assisted interventions in gastroenterology and surgery.

Sustainable Development Goals3 Good health and well-being
Middlesex University ThemeHealth & Wellbeing
PublisherSpringer
JournalNature Reviews Gastroenterology and Hepatology
ISSN1759-5045
Electronic1759-5053
Publication dates
Online09 Nov 2022
PrintMar 2023
Publication process dates
Accepted03 Oct 2022
Deposited12 Feb 2024
Output statusPublished
Accepted author manuscript
File Access Level
Open
Digital Object Identifier (DOI)https://doi.org/10.1038/s41575-022-00701-y
Web of Science identifierWOS:000880507000002
LanguageEnglish
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