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
Type | Article |
---|---|
Title | Artificial intelligence and automation in endoscopy and surgery |
Authors | Chadebecq, 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 Goals | 3 Good health and well-being |
Middlesex University Theme | Health & Wellbeing |
Publisher | Springer |
Journal | Nature Reviews Gastroenterology and Hepatology |
ISSN | 1759-5045 |
Electronic | 1759-5053 |
Publication dates | |
Online | 09 Nov 2022 |
Mar 2023 | |
Publication process dates | |
Accepted | 03 Oct 2022 |
Deposited | 12 Feb 2024 |
Output status | Published |
Accepted author manuscript | File Access Level Open |
Digital Object Identifier (DOI) | https://doi.org/10.1038/s41575-022-00701-y |
Web of Science identifier | WOS:000880507000002 |
Language | English |
https://repository.mdx.ac.uk/item/z8099
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