TY - JOUR
T1 - Artificial intelligence and neural networks in urology
T2 - current clinical applications
AU - Uro-technology and SoMe Working Group of the Young Academic Urologists Working Party of the European Association of Urology
AU - Checcucci, Enrico
AU - Autorino, Riccardo
AU - Cacciamani, Giovanni E.
AU - Amparore, Daniele
AU - De Cillis, Sabrina
AU - Piana, Alberto
AU - Piazzolla, Pietro
AU - Vezzetti, Enrico
AU - Fiori, Cristian
AU - Veneziano, Domenico
AU - Tewari, Ash
AU - Dasgupta, Prokar
AU - Hung, Andrew
AU - Gill, Inderbir
AU - Porpiglia, Francesco
PY - 2020/2/1
Y1 - 2020/2/1
N2 - INTRODUCTION: As we enter the era of "big data," an increasing amount of complex health-care data will become available. These data are often redundant, "noisy," and characterized by wide variability. In order to offer a precise and transversal view of a clinical scenario the artificial intelligence (AI) with machine learning (ML) algorithms and Artificial neuron networks (ANNs) process were adopted, with a promising wide diffusion in the near future. The present work aims to provide a comprehensive and critical overview of the current and potential applications of AI and ANNs in urology. EVIDENCE ACQUISITION: A non-systematic review of the literature was performed by screening Medline, PubMed, the Cochrane Database, and Embase to detect pertinent studies regarding the application of AI and ANN in Urology. EVIDENCE SYNTHESIS: The main application of AI in urology is the field of genitourinary cancers. Focusing on prostate cancer, AI was applied for the prediction of prostate biopsy results. For bladder cancer, the prediction of recurrence-free probability and diagnostic evaluation were analysed with ML algorithms. For kidney and testis cancer, anecdotal experiences were reported for staging and prediction of diseases recurrence. More recently, AI has been applied in non-oncological diseases like stones and functional urology. CONCLUSIONS: AI technologies are growing their role in health care; but, up to now, their "real-life" implementation remains limited. However, in the near future, the potential of AI-driven era could change the clinical practice in Urology, improving overall patient outcomes.
AB - INTRODUCTION: As we enter the era of "big data," an increasing amount of complex health-care data will become available. These data are often redundant, "noisy," and characterized by wide variability. In order to offer a precise and transversal view of a clinical scenario the artificial intelligence (AI) with machine learning (ML) algorithms and Artificial neuron networks (ANNs) process were adopted, with a promising wide diffusion in the near future. The present work aims to provide a comprehensive and critical overview of the current and potential applications of AI and ANNs in urology. EVIDENCE ACQUISITION: A non-systematic review of the literature was performed by screening Medline, PubMed, the Cochrane Database, and Embase to detect pertinent studies regarding the application of AI and ANN in Urology. EVIDENCE SYNTHESIS: The main application of AI in urology is the field of genitourinary cancers. Focusing on prostate cancer, AI was applied for the prediction of prostate biopsy results. For bladder cancer, the prediction of recurrence-free probability and diagnostic evaluation were analysed with ML algorithms. For kidney and testis cancer, anecdotal experiences were reported for staging and prediction of diseases recurrence. More recently, AI has been applied in non-oncological diseases like stones and functional urology. CONCLUSIONS: AI technologies are growing their role in health care; but, up to now, their "real-life" implementation remains limited. However, in the near future, the potential of AI-driven era could change the clinical practice in Urology, improving overall patient outcomes.
KW - Artificial intelligence
KW - Big data
KW - Urologic neoplasms
KW - Urology
UR - http://www.scopus.com/inward/record.url?scp=85081154119&partnerID=8YFLogxK
U2 - 10.23736/S0393-2249.19.03613-0
DO - 10.23736/S0393-2249.19.03613-0
M3 - Review article
C2 - 31833725
SN - 1827-1758
VL - 72
SP - 49
EP - 57
JO - Minerva urologica e nefrologica = The Italian journal of urology and nephrology
JF - Minerva urologica e nefrologica = The Italian journal of urology and nephrology
IS - 1
ER -
