Artificial intelligence and simulation in urology.

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Tytuł:: Artificial intelligence and simulation in urology.
Autorzy:: Gómez Rivas J; Departamento de Urología, Hospital Clínico San Carlos, Madrid, Spain; Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, The Netherlands. Electronic address: .
Toribio Vázquez C; Departamento de Urología, Hospital Universitario La Paz, Madrid, Spain.
Ballesteros Ruiz C; Departamento de Urología, Hospital Universitario La Paz, Madrid, Spain.
Taratkin M; Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, The Netherlands; Institute for Urology and Reproductive Health, Sechenov University, Moscú, Russia.
Marenco JL; Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, The Netherlands; Departamento de Urología, Instituto Valenciano de Oncología, Valencia, Spain.
Cacciamani GE; Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, The Netherlands; Catherine and Joseph Aresty Department of Urology, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
Checcucci E; Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, The Netherlands; Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Orbassano, Italy.
Okhunov Z; Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, The Netherlands; Department of Urology, University of California, Irvine, CA, United States.
Enikeev D; Institute for Urology and Reproductive Health, Sechenov University, Moscú, Russia.
Esperto F; Department of Urology, Campus Biomedico, University of Rome, Roma, Italy.
Grossmann R; Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, The Netherlands; Eastern Maine Medical Center, Bangor, ME, United States.
Somani B; Department of Urology, University Hospital Southhampton, Southampton, United Kingdom.
Veneziano D; Young Academic Urologist-Urotechnology Working Party (ESUT-YAU), European Association of Urology, Arnhem, The Netherlands; Department of Urology and Kidney Transplant, Grande Ospedale Metropolitano, Reggio Calabria, Italy.
Źródło:: Actas urologicas espanolas [Actas Urol Esp (Engl Ed)] 2021 Oct; Vol. 45 (8), pp. 524-529. Date of Electronic Publication: 2021 Sep 12.
Typ publikacji:: Journal Article; Review
Język:: English; Spanish; Castilian
Imprint Name(s):: Original Publication: Madrid : Elsevier España
MeSH Terms:: Medicine*
Urology*
Artificial Intelligence ; Computer Simulation ; Diagnostic Imaging ; Humans
Contributed Indexing:: Keywords: Aprendizaje automático; Artificial intelligence; Entrenamiento; Inteligencia artificial; Machine learning; Training; Urology; Urología
Entry Date(s):: Date Created: 20210916 Date Completed: 20211108 Latest Revision: 20211108
Update Code:: 20240105
DOI:: 10.1016/j.acuroe.2021.07.001
PMID:: 34526254
: Czasopismo naukowe

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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.
(Copyright © 2021 AEU. Published by Elsevier España, S.L.U. All rights reserved.)

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