Cargando…

Artificial Intelligence in Urooncology: What We Have and What We Expect

SIMPLE SUMMARY: Our study provides an overview of the current state of artificial intelligence applications in urooncology and explores potential future advancements in this field. With remarkable progress already achieved, artificial intelligence has revolutionized urooncology by facilitating image...

Descripción completa

Detalles Bibliográficos
Autores principales: Froń, Anita, Semianiuk, Alina, Lazuk, Uladzimir, Ptaszkowski, Kuba, Siennicka, Agnieszka, Lemiński, Artur, Krajewski, Wojciech, Szydełko, Tomasz, Małkiewicz, Bartosz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10486651/
https://www.ncbi.nlm.nih.gov/pubmed/37686558
http://dx.doi.org/10.3390/cancers15174282
_version_ 1785103057174921216
author Froń, Anita
Semianiuk, Alina
Lazuk, Uladzimir
Ptaszkowski, Kuba
Siennicka, Agnieszka
Lemiński, Artur
Krajewski, Wojciech
Szydełko, Tomasz
Małkiewicz, Bartosz
author_facet Froń, Anita
Semianiuk, Alina
Lazuk, Uladzimir
Ptaszkowski, Kuba
Siennicka, Agnieszka
Lemiński, Artur
Krajewski, Wojciech
Szydełko, Tomasz
Małkiewicz, Bartosz
author_sort Froń, Anita
collection PubMed
description SIMPLE SUMMARY: Our study provides an overview of the current state of artificial intelligence applications in urooncology and explores potential future advancements in this field. With remarkable progress already achieved, artificial intelligence has revolutionized urooncology by facilitating image analysis, grading, biomarker research, and treatment planning. We also discuss types of artificial intelligence and their possible applications in the management of cancers such as prostate, kidney, bladder, and testicular. As artificial intelligence technology continues to evolve, it holds immense promise for further advancing urooncology and enhancing the care of patients with cancer. ABSTRACT: Introduction: Artificial intelligence is transforming healthcare by driving innovation, automation, and optimization across various fields of medicine. The aim of this study was to determine whether artificial intelligence (AI) techniques can be used in the diagnosis, treatment planning, and monitoring of urological cancers. Methodology: We conducted a thorough search for original and review articles published until 31 May 2022 in the PUBMED/Scopus database. Our search included several terms related to AI and urooncology. Articles were selected with the consensus of all authors. Results: Several types of AI can be used in the medical field. The most common forms of AI are machine learning (ML), deep learning (DL), neural networks (NNs), natural language processing (NLP) systems, and computer vision. AI can improve various domains related to the management of urologic cancers, such as imaging, grading, and nodal staging. AI can also help identify appropriate diagnoses, treatment options, and even biomarkers. In the majority of these instances, AI is as accurate as or sometimes even superior to medical doctors. Conclusions: AI techniques have the potential to revolutionize the diagnosis, treatment, and monitoring of urologic cancers. The use of AI in urooncology care is expected to increase in the future, leading to improved patient outcomes and better overall management of these tumors.
format Online
Article
Text
id pubmed-10486651
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-104866512023-09-09 Artificial Intelligence in Urooncology: What We Have and What We Expect Froń, Anita Semianiuk, Alina Lazuk, Uladzimir Ptaszkowski, Kuba Siennicka, Agnieszka Lemiński, Artur Krajewski, Wojciech Szydełko, Tomasz Małkiewicz, Bartosz Cancers (Basel) Review SIMPLE SUMMARY: Our study provides an overview of the current state of artificial intelligence applications in urooncology and explores potential future advancements in this field. With remarkable progress already achieved, artificial intelligence has revolutionized urooncology by facilitating image analysis, grading, biomarker research, and treatment planning. We also discuss types of artificial intelligence and their possible applications in the management of cancers such as prostate, kidney, bladder, and testicular. As artificial intelligence technology continues to evolve, it holds immense promise for further advancing urooncology and enhancing the care of patients with cancer. ABSTRACT: Introduction: Artificial intelligence is transforming healthcare by driving innovation, automation, and optimization across various fields of medicine. The aim of this study was to determine whether artificial intelligence (AI) techniques can be used in the diagnosis, treatment planning, and monitoring of urological cancers. Methodology: We conducted a thorough search for original and review articles published until 31 May 2022 in the PUBMED/Scopus database. Our search included several terms related to AI and urooncology. Articles were selected with the consensus of all authors. Results: Several types of AI can be used in the medical field. The most common forms of AI are machine learning (ML), deep learning (DL), neural networks (NNs), natural language processing (NLP) systems, and computer vision. AI can improve various domains related to the management of urologic cancers, such as imaging, grading, and nodal staging. AI can also help identify appropriate diagnoses, treatment options, and even biomarkers. In the majority of these instances, AI is as accurate as or sometimes even superior to medical doctors. Conclusions: AI techniques have the potential to revolutionize the diagnosis, treatment, and monitoring of urologic cancers. The use of AI in urooncology care is expected to increase in the future, leading to improved patient outcomes and better overall management of these tumors. MDPI 2023-08-26 /pmc/articles/PMC10486651/ /pubmed/37686558 http://dx.doi.org/10.3390/cancers15174282 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Froń, Anita
Semianiuk, Alina
Lazuk, Uladzimir
Ptaszkowski, Kuba
Siennicka, Agnieszka
Lemiński, Artur
Krajewski, Wojciech
Szydełko, Tomasz
Małkiewicz, Bartosz
Artificial Intelligence in Urooncology: What We Have and What We Expect
title Artificial Intelligence in Urooncology: What We Have and What We Expect
title_full Artificial Intelligence in Urooncology: What We Have and What We Expect
title_fullStr Artificial Intelligence in Urooncology: What We Have and What We Expect
title_full_unstemmed Artificial Intelligence in Urooncology: What We Have and What We Expect
title_short Artificial Intelligence in Urooncology: What We Have and What We Expect
title_sort artificial intelligence in urooncology: what we have and what we expect
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10486651/
https://www.ncbi.nlm.nih.gov/pubmed/37686558
http://dx.doi.org/10.3390/cancers15174282
work_keys_str_mv AT fronanita artificialintelligenceinurooncologywhatwehaveandwhatweexpect
AT semianiukalina artificialintelligenceinurooncologywhatwehaveandwhatweexpect
AT lazukuladzimir artificialintelligenceinurooncologywhatwehaveandwhatweexpect
AT ptaszkowskikuba artificialintelligenceinurooncologywhatwehaveandwhatweexpect
AT siennickaagnieszka artificialintelligenceinurooncologywhatwehaveandwhatweexpect
AT leminskiartur artificialintelligenceinurooncologywhatwehaveandwhatweexpect
AT krajewskiwojciech artificialintelligenceinurooncologywhatwehaveandwhatweexpect
AT szydełkotomasz artificialintelligenceinurooncologywhatwehaveandwhatweexpect
AT małkiewiczbartosz artificialintelligenceinurooncologywhatwehaveandwhatweexpect