Prostate cancer (PCa) is the most frequent urological malignancy in men worldwide. DNA methylation has an essential role in the etiology and pathogenesis of PCa. The purpose of the present study was to identify the aberrantly methylated‑differentiall...
Journal of applied clinical medical physics
Dec 9, 2019
PURPOSE: Knowledge-based planning (KBP) techniques have been reported to improve plan quality, efficiency, and consistency in radiation therapy. However, plan complexity and deliverability have not been addressed previously for treatment plans guided...
In the current clinical care practice, Gleason grading system is one of the most powerful prognostic predictors for prostate cancer (PCa). The grading system is based on the architectural pattern of cancerous epithelium in histological images. Howeve...
BACKGROUND: The pathologic diagnosis and Gleason grading of prostate cancer are time-consuming, error-prone, and subject to interobserver variability. Machine learning offers opportunities to improve the diagnosis, risk stratification, and prognostic...
PURPOSE: Several guidelines recommend pelvic lymph node dissection (PLND) at robot-assisted radical prostatectomy (RARP) only when lymph node involvement (LN+) is >2%. Individual surgeon use of PLND is not well-known. We sought to examine variability...
BACKGROUND: Prediction of lymph node invasion (LNI) after radical prostatectomy has been rarely assessed in robotically assisted laparoscopic radical prostatectomy (RALP) series. We aimed to develop and externally validate a pretreatment nomogram for...
PURPOSE: The purpose of the study was to provide a comprehensive review of recent machine learning (ML) and deep learning (DL) applications in urological practice. Numerous studies have reported their use in the medical care of various urological dis...
Deep learning algorithms have achieved great success in cancer image classification. However, it is imperative to understand the differences between the deep learning and human approaches. Using an explainable model, we aimed to compare the deep lear...
The purpose of this work is to validate the application of a deep learning-based method for pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy treatment planning. We propose to integrate dense block minimization in...
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