Artificial Intelligence in the Advanced Diagnosis of Bladder Cancer-Comprehensive Literature Review and Future Advancement-Reference-Cited by-同舟云学术

Artificial Intelligence in the Advanced Diagnosis of Bladder Cancer-Comprehensive Literature Review and Future Advancement

Published:2023-07-07 Issue:13 Volume:13 Page:2308
ISSN:2075-4418
Container-title:Diagnostics
language:en
Short-container-title:Diagnostics

Author:

Ferro Matteo¹^ORCID,Falagario Ugo Giovanni²,Barone Biagio³^ORCID,Maggi Martina⁴^ORCID,Crocetto Felice⁵^ORCID,Busetto Gian Maria²^ORCID,Giudice Francesco del⁴^ORCID,Terracciano Daniela⁶^ORCID,Lucarelli Giuseppe⁷^ORCID,Lasorsa Francesco⁷^ORCID,Catellani Michele⁸^ORCID,Brescia Antonio¹^ORCID,Mistretta Francesco Alessandro¹⁹^ORCID,Luzzago Stefano¹⁹,Piccinelli Mattia Luca¹^ORCID,Vartolomei Mihai Dorin¹⁰^ORCID,Jereczek-Fossa Barbara Alicja⁹¹¹,Musi Gennaro¹⁹,Montanari Emanuele¹²¹³,Cobelli Ottavio de¹⁹,Tataru Octavian Sabin¹⁴^ORCID

Affiliation:

1. Department of Urology, IEO—European Institute of Oncology, IRCCS—Istituto di Ricovero e Cura a Carattere Scientifico, 20141 Milan, Italy

2. Department of Urology and Organ Transplantation, University of Foggia, 71121 Foggia, Italy

3. Urology Unit, Department of Surgical Sciences, AORN Sant’Anna e San Sebastiano, 81100 Caserta, Italy

4. Department of Maternal Infant and Urologic Sciences, Policlinico Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy

5. Department of Neurosciences and Reproductive Sciences and Odontostomatology, University of Naples Federico II, 80131 Naples, Italy

6. Department of Translational Medical Sciences, University of Naples “Federico II”, 80131 Naples, Italy

7. Urology, Andrology and Kidney Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari, 70124 Bari, Italy

8. Department of Urology, ASST Papa Giovanni XXIII, 24127 Bergamo, Italy

9. Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy

10. Department of Urology, Medical University of Vienna, 1090 Vienna, Austria

11. Division of Radiation Oncology, IEO—European Institute of Oncology IRCCS, 20141 Milan, Italy

12. Department of Urology, Foundation IRCCS Ca’ Granda—Ospedale Maggiore Policlinico, 20122 Milan, Italy

13. Department of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy

14. Department of Simulation Applied in Medicine, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mures, 540142 Târgu Mures, Romania

Abstract

Artificial intelligence is highly regarded as the most promising future technology that will have a great impact on healthcare across all specialties. Its subsets, machine learning, deep learning, and artificial neural networks, are able to automatically learn from massive amounts of data and can improve the prediction algorithms to enhance their performance. This area is still under development, but the latest evidence shows great potential in the diagnosis, prognosis, and treatment of urological diseases, including bladder cancer, which are currently using old prediction tools and historical nomograms. This review focuses on highly significant and comprehensive literature evidence of artificial intelligence in the management of bladder cancer and investigates the near introduction in clinical practice.

Publisher

MDPI AG

Subject

Clinical Biochemistry

Link

https://www.mdpi.com/2075-4418/13/13/2308/pdf

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