Artificial intelligence and simulation in urology
Actas Urol Esp (Engl Ed). 2021 Jun 11:S0210-4806(21)00088-7.
doi: 10.1016/j.acuro.2020.10.012.
Online ahead of print.
[Article in
English,
Spanish]
Authors
J Gómez Rivas
1
, C Toribio Vázquez
2
, C Ballesteros Ruiz
2
, M Taratkin
3
, J L Marenco
4
, G E Cacciamani
5
, E Checcucci
6
, Z Okhunov
7
, D Enikeev
8
, F Esperto
9
, R Grossmann
10
, B Somani
11
, D Veneziano
12
Affiliations
- 1 Departamento de Urología, Hospital Clínico San Carlos, Madrid, España; Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, Países Bajos. Electronic address: [email protected].
- 2 Departamento de Urología, Hospital Universitario La Paz, Madrid, España.
- 3 Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, Países Bajos; Institute for Urology and Reproductive Health, Sechenov University, Moscú, Rusia.
- 4 Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, Países Bajos; Departamento de Urología, Instituto Valenciano de Oncología, Valencia, España.
- 5 Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, Países Bajos; Catherine and Joseph Aresty Department of Urology, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, Estados Unidos.
- 6 Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, Países Bajos; Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Orbassano, Italia.
- 7 Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, Países Bajos; Department of Urology, University of California, Irvine, California, Estados Unidos.
- 8 Institute for Urology and Reproductive Health, Sechenov University, Moscú, Rusia.
- 9 Department of Urology, Campus Biomedico, University of Rome, Roma, Italia.
- 10 Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, Países Bajos; Eastern Maine Medical Center, Bangor, Maine, Estados Unidos.
- 11 Department of Urology, University Hospital Southhampton, Southampton, Reino Unido.
- 12 Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, Países Bajos; Department of Urology and Kidney Transplant, Grande Ospedale Metropolitano, Reggio Calabria, Italia.
Abstract
Introduction and objective:
Artificial intelligence (AI) is in full development and its implementation in medicine has led to an improvement in clinical and surgical practice. One of its multiple applications is surgical training, with the creation of programs that allow avoiding complications and risks for the patient. The aim of this article is to analyze the advantages of AI applied to surgical training in urology.
Material and methods:
A literary research is carried out to identify articles published in English regarding AI applied to medicine, especially in surgery and the acquisition of surgical skills.
Results:
Surgical training has evolved over time thanks to AI. A model for surgical learning where skills are acquired in a progressive way while avoiding complications to the patient, has been created. The use of simulators allows a progressive learning, providing trainees with procedures that increase in number and complexity. On the other hand, AI is used in imaging tests for surgical or treatment planning.
Conclusion:
Currently, the use of AI in daily clinical practice has led to progress in medicine, specifically in surgical training.
Keywords:
Aprendizaje automático; Artificial intelligence; Entrenamiento; Inteligencia artificial; Machine learning; Training; Urology; Urología.
Copyright © 2021 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.