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...
Autores principales: | , , , , , , , , |
---|---|
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 |