Refereed review article in scientific journal (A2)
Artificial Intelligence in Surgical Learning
List of Authors: Pakkasjärvi Niklas, Luthra Tanvi, Anand Sachit
Publisher: MDPI
Publication year: 2023
Journal: Surgeries
Journal name in source: Surgeries (Switzerland)
Volume number: 4
Issue number: 1
Start page: 86
End page: 97
eISSN: 2673-4095
DOI: http://dx.doi.org/10.3390/surgeries4010010
URL: https://doi.org/10.3390/surgeries4010010
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/179842300
(1) Background: Artificial Intelligence (AI) is transforming healthcare on all levels. While AI shows immense potential, the clinical implementation is lagging. We present a concise review of AI in surgical learning;
(2) Methods: A non-systematic review of AI in surgical learning of the literature in English is provided;
(3) Results: AI shows utility for all components of surgical competence within surgical learning. AI presents with great potential within robotic surgery specifically;
(4) Conclusions: Technology will evolve in ways currently unimaginable, presenting us with novel applications of AI and derivatives thereof. Surgeons must be open to new modes of learning to be able to implement all evidence-based applications of AI in the future. Systematic analyses of AI in surgical learning are needed.
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