: 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.

Artificial Intelligence in the Advanced Diagnosis of Bladder Cancer-Comprehensive Literature Review and Future Advancement / Ferro, Matteo; Falagario, Ugo Giovanni; Barone, Biagio; Maggi, Martina; Crocetto, Felice; Busetto, Gian Maria; Giudice, Francesco del; Terracciano, Daniela; Lucarelli, Giuseppe; Lasorsa, Francesco; Catellani, Michele; Brescia, Antonio; Mistretta, Francesco Alessandro; Luzzago, Stefano; Piccinelli, Mattia Luca; Vartolomei, Mihai Dorin; Jereczek-Fossa, Barbara Alicja; Musi, Gennaro; Montanari, Emanuele; Cobelli, Ottavio de; Tataru, Octavian Sabin. - In: DIAGNOSTICS. - ISSN 2075-4418. - 13:13(2023). [10.3390/diagnostics13132308]

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

Ferro, Matteo;Barone, Biagio;Crocetto, Felice;Terracciano, Daniela;Brescia, Antonio;Musi, Gennaro;
2023

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.
2023
Artificial Intelligence in the Advanced Diagnosis of Bladder Cancer-Comprehensive Literature Review and Future Advancement / Ferro, Matteo; Falagario, Ugo Giovanni; Barone, Biagio; Maggi, Martina; Crocetto, Felice; Busetto, Gian Maria; Giudice, Francesco del; Terracciano, Daniela; Lucarelli, Giuseppe; Lasorsa, Francesco; Catellani, Michele; Brescia, Antonio; Mistretta, Francesco Alessandro; Luzzago, Stefano; Piccinelli, Mattia Luca; Vartolomei, Mihai Dorin; Jereczek-Fossa, Barbara Alicja; Musi, Gennaro; Montanari, Emanuele; Cobelli, Ottavio de; Tataru, Octavian Sabin. - In: DIAGNOSTICS. - ISSN 2075-4418. - 13:13(2023). [10.3390/diagnostics13132308]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/961420
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