2017
DOI: 10.1016/j.ijrobp.2017.06.1189
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Machine Learning to Predict Postradical Prostatectomy Pathology Outcomes in Intermediate Risk Prostate Cancer

Abstract: Purpose/Objective(s): Although rare, the incidence of bilateral testicular germ cell tumors (GCTs) has increased over time. Using the Surveillance, Epidemiology, and End Results (SEER) database, we describe the prevalence, characteristics, and outcomes of bilateral testicular GCTs, as well as the impact of prior radiotherapy on development of a metachronous GCT. Materials/Methods: A total of 757 cases of bilateral and 42,713 cases of unilateral testicular GCTs treated 1973-2013 were identified in the SEER data… Show more

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“…This research work focused on prostate cancer classification. Since the prediction of disease‐free survival is the ultima goal in clinical trial, we will further collect data and develop suitable models for survival prediction to promote the deep learning‐based radiomics.…”
Section: Discussionmentioning
confidence: 99%
“…This research work focused on prostate cancer classification. Since the prediction of disease‐free survival is the ultima goal in clinical trial, we will further collect data and develop suitable models for survival prediction to promote the deep learning‐based radiomics.…”
Section: Discussionmentioning
confidence: 99%