Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2023 Aug 26;15(17):4282.
doi: 10.3390/cancers15174282.

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

Anita Froń  1 , Alina Semianiuk  1 , Uladzimir Lazuk  1 , Kuba Ptaszkowski  2 , Agnieszka Siennicka  3 , Artur Lemiński  4 , Wojciech Krajewski  1 , Tomasz Szydełko  1 , Bartosz Małkiewicz  1
Affiliations
Review

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

Anita Froń et al. Cancers (Basel). .

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.

Keywords: artificial intelligence; machine learning; prostate cancer; urooncology.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Subfields of Artificial Intelligence.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Hamet P., Tremblay J. Artificial intelligence in medicine. Metabolism. 2017;69:S36–S40. doi: 10.1016/j.metabol.2017.01.011. - DOI - PubMed
    1. van der Laak J., Litjens G., Ciompi F. Deep learning in histopathology: The path to the clinic. Nat. Med. 2021;27:775–784. doi: 10.1038/s41591-021-01343-4. - DOI - PubMed
    1. Pantanowitz L., Quiroga-Garza G.M., Bien L., Heled R., Laifenfeld D., Linhart C., Sandbank J., Shach A.A., Shalev V., Vecsler M., et al. An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: A blinded clinical validation and deployment study. Lancet Digit. Health. 2020;2:e407–e416. doi: 10.1016/S2589-7500(20)30159-X. - DOI - PubMed
    1. Shah M., Naik N., Somani B.K., Hameed B.Z. Artificial intelligence (AI) in urology-Current use and future directions: An iTRUE study. Turk. J. Urol. 2020;46:S27–S39. doi: 10.5152/tud.2020.20117. - DOI - PMC - PubMed
    1. Rodrigues J.A., Krois J., Schwendicke F. Demystifying artificial intelligence and deep learning in dentistry. Braz. Oral Res. 2021;35:e094. doi: 10.1590/1807-3107bor-2021.vol35.0094. - DOI - PubMed

LinkOut - more resources