Development of Machine Learning Algorithm to Predict the Risk of Incontinence After Robot-Assisted Radical Prostatectomy-Reference-Cited by-同舟云学术

Development of Machine Learning Algorithm to Predict the Risk of Incontinence After Robot-Assisted Radical Prostatectomy

Published:2024-08-01 Issue:8 Volume:38 Page:871-878
ISSN:0892-7790
Container-title:Journal of Endourology
language:en
Short-container-title:Journal of Endourology

Author:

Amparore Daniele¹,De Cillis Sabrina¹,Alladio Eugenio²³,Sica Michele⁴,Piramide Federico¹,Verri Paolo¹^ORCID,Checcucci Enrico⁴,Piana Alberto¹,Quarà Alberto¹,Cisero Edoardo¹,Manfredi Matteo¹,Di Dio Michele⁵,Fiori Cristian¹,Porpiglia Francesco¹

Affiliation:

1. Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy.

2. Department of Chemistry, University of Turin, Turin, Italy.

3. Centro Regionale Antidoping “A. Bertinaria” of Orbassano (Turin), Turin, Italy.

4. Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy.

5. Division of Urology, Department of Surgery, SS Annunziata Hospital, Cosenza, Italy.

Publisher

Mary Ann Liebert Inc

Link

https://www.liebertpub.com/doi/pdf/10.1089/end.2024.0057

Reference30 articles.

1. 2022 Update on Prostate Cancer Epidemiology and Risk Factors—A Systematic Review

2. Sexual and urinary function in prostate cancer clinical studies and the Europa Uomo Patient Reported Outcome Study: does it match?

3. Total anatomical reconstruction during robot-assisted radical prostatectomy: focus on urinary continence recovery and related complications after 1000 procedures

4. The importance of anatomical reconstruction for continence recovery after robot assisted radical prostatectomy: a systematic review and pooled analysis from referral centers

5. Improvement of Continence Rate with Pelvic Floor Muscle Training Post-Prostatectomy: A Meta-Analysis of Randomized Controlled Trials

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