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ENDOUROLOGY - Invited Review

Artificial intelligence (AI) in urology-Current use and future directions: An iTRUE study

Milap Shah 1 2 , Nithesh Naik 2 3 , Bhaskar K. Somani 2 4 , BM Zeeshan Hameed 1 2 5
1.

Department of Urology, Kasturba Medical College Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India

2.

i-TRUE: International Training and Research in Uro-oncology and Endourology, Manipal, Karnataka, India

3.

Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India

4.

Department of Urological Surgery, University Hospital Southampton NHS Trust, Southampton, UK

5.

KMC Innovation Centre, Manipal Academy of Higher Education, Manipal, Karnataka, India

Urol Res Pract 2020; 46: Supplement S27-S39
DOI: 10.5152/tud.2020.20117
Keywords : Artificial intelligence; deep learning; machine learning; prostate cancer; urolithiasis; urology.
Read: 5080 Downloads: 886 Published: 27 May 2020
Volume 46, Issue 1, November 2020
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Objective: Artificial intelligence (AI) is used in various urological conditions such as urolithiasis, pediatric urology, urogynecology, benign prostate hyperplasia (BPH), renal transplant, and uro-oncology. The various models of AI and its application in urology subspecialties are reviewed and discussed.

Material and methods: Search strategy was adapted to identify and review the literature pertaining to the application of AI in urology using the keywords “urology,” “artificial intelligence,” “machine learning,” “deep learning,” “artificial neural networks,” “computer vision,” and “natural language processing” were included and categorized. Review articles, editorial comments, and non-urologic studies were excluded.

Results: The article reviewed 47 articles that reported characteristics and implementation of AI in urological cancer. In all cases with benign conditions, artificial intelligence was used to predict outcomes of the surgical procedure. In urolithiasis, it was used to predict stone composition, whereas in pediatric urology and BPH, it was applied to predict the severity of condition. In cases with malignant conditions, it was applied to predict the treatment response, survival, prognosis, and recurrence on the basis of the genomic and biomarker studies. These results were also found to be statistically better than routine approaches. Application of radiomics in classification and nuclear grading of renal masses, cystoscopic diagnosis of bladder cancers, predicting Gleason score, and magnetic resonance imaging with  computer-assisted diagnosis for prostate cancers are  few applications of AI that have been studied extensively.

Conclusions: In the near future, we will see a shift in the clinical paradigm as AI applications will find their place in the guidelines and revolutionize the decision-making process.

Cite this article as: Shah M, Naik N, Somani BK, Hameed BMZ. Artificial intelligence (AI) in urology-Current use and future directions: An iTRUE study. Turk J Urol 2020; 46(Supp. 1): S27-S39.

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