Artificial Intelligence in Urooncology: What We Have and What We Expect
- PMID: 37686558
- PMCID: PMC10486651
- DOI: 10.3390/cancers15174282
Artificial Intelligence in Urooncology: What We Have and What We Expect
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.
Conflict of interest statement
The authors declare no conflict of interest.
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References
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- 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
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