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

Autor: Ferro M; Department of Urology, IEO-European Institute of Oncology, IRCCS-Istituto di Ricovero e Cura a Carattere Scientifico, 20141 Milan, Italy., Falagario UG; Department of Urology and Organ Transplantation, University of Foggia, 71121 Foggia, Italy., Barone B; Urology Unit, Department of Surgical Sciences, AORN Sant'Anna e San Sebastiano, 81100 Caserta, Italy., Maggi M; Department of Maternal Infant and Urologic Sciences, Policlinico Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy., Crocetto F; Department of Neurosciences and Reproductive Sciences and Odontostomatology, University of Naples Federico II, 80131 Naples, Italy., Busetto GM; Department of Urology and Organ Transplantation, University of Foggia, 71121 Foggia, Italy., Giudice FD; Department of Maternal Infant and Urologic Sciences, Policlinico Umberto I Hospital, Sapienza University of Rome, 00161 Rome, Italy., Terracciano D; Department of Translational Medical Sciences, University of Naples 'Federico II', 80131 Naples, Italy., Lucarelli G; Urology, Andrology and Kidney Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari, 70124 Bari, Italy., Lasorsa F; Urology, Andrology and Kidney Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari, 70124 Bari, Italy., Catellani M; Department of Urology, ASST Papa Giovanni XXIII, 24127 Bergamo, Italy., Brescia A; Department of Urology, IEO-European Institute of Oncology, IRCCS-Istituto di Ricovero e Cura a Carattere Scientifico, 20141 Milan, Italy., Mistretta FA; Department of Urology, IEO-European Institute of Oncology, IRCCS-Istituto di Ricovero e Cura a Carattere Scientifico, 20141 Milan, Italy.; Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy., Luzzago S; Department of Urology, IEO-European Institute of Oncology, IRCCS-Istituto di Ricovero e Cura a Carattere Scientifico, 20141 Milan, Italy.; Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy., Piccinelli ML; Department of Urology, IEO-European Institute of Oncology, IRCCS-Istituto di Ricovero e Cura a Carattere Scientifico, 20141 Milan, Italy., Vartolomei MD; Department of Urology, Medical University of Vienna, 1090 Vienna, Austria., Jereczek-Fossa BA; Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy.; Division of Radiation Oncology, IEO-European Institute of Oncology IRCCS, 20141 Milan, Italy., Musi G; Department of Urology, IEO-European Institute of Oncology, IRCCS-Istituto di Ricovero e Cura a Carattere Scientifico, 20141 Milan, Italy.; Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy., Montanari E; Department of Urology, Foundation IRCCS Ca' Granda-Ospedale Maggiore Policlinico, 20122 Milan, Italy.; Department of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy., Cobelli O; Department of Urology, IEO-European Institute of Oncology, IRCCS-Istituto di Ricovero e Cura a Carattere Scientifico, 20141 Milan, Italy.; Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy., Tataru OS; Department of Simulation Applied in Medicine, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mures, 540142 Târgu Mures, Romania.
Jazyk: angličtina
Zdroj: Diagnostics (Basel, Switzerland) [Diagnostics (Basel)] 2023 Jul 07; Vol. 13 (13). Date of Electronic Publication: 2023 Jul 07.
DOI: 10.3390/diagnostics13132308
Abstrakt: 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.
Databáze: MEDLINE
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