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Erschienen in: European Journal of Trauma and Emergency Surgery 3/2021

26.07.2020 | Review Article

The automaton as a surgeon: the future of artificial intelligence in emergency and general surgery

verfasst von: Lara Rimmer, Callum Howard, Leonardo Picca, Mohamad Bashir

Erschienen in: European Journal of Trauma and Emergency Surgery | Ausgabe 3/2021

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Abstract

Background

Artificial intelligence (AI) is a field involving computational simulation of human intelligence processes; these applications of deep learning could have implications in the specialty of emergency surgery (ES). ES is a rapidly advancing area, and this review will outline the most recent advances.

Methods

A literature search encompassing the uses of AI in surgery was conducted across large databases (Pubmed, OVID, SCOPUS). Two doctors (LR, CH) both collated relevant papers and appraised them. Papers included were published within the last 5 years, and a “snowball effect” used to collate further relevant literature.

Results

AI has been shown to provide value in predicting surgical outcomes and giving personalised patient risks based on inputted data. Further to this, image recognition technology within AI has showed success in fracture identification and breast cancer diagnosis. Regarding theatre presence, supervised robots have carried out suturing and anastomosis of bowel in controlled environments to a high standard.

Conclusion

AI has potential for integration across surgical services, from diagnosis to treatment, and aiding the surgeon in key decision-making for risks per patient. Fully automated surgery may be the future, but at present, AI needs human supervision.
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Metadaten
Titel
The automaton as a surgeon: the future of artificial intelligence in emergency and general surgery
verfasst von
Lara Rimmer
Callum Howard
Leonardo Picca
Mohamad Bashir
Publikationsdatum
26.07.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
European Journal of Trauma and Emergency Surgery / Ausgabe 3/2021
Print ISSN: 1863-9933
Elektronische ISSN: 1863-9941
DOI
https://doi.org/10.1007/s00068-020-01444-8

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