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Prostatectomy

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A novel assessment of whole-mount Gleason grading in prostate cancer to identify candidates for radical prostatectomy: a machine learning-based multiomics study.

Theranostics
: This study aims to assess whole-mount Gleason grading (GG) in prostate cancer (PCa) accurately using a multiomics machine learning (ML) model and to compare its performance with biopsy-proven GG (bxGG) assessment. : A total of 146 patients with PCa...

Advancements in artificial intelligence for robotic-assisted radical prostatectomy in men suffering from prostate cancer: results from a scoping review.

Chinese clinical oncology
BACKGROUND: Robotic-assisted radical prostatectomy (RARP) is currently a first-line treatment option for men with localized prostate cancer (PCa), at least 10 years of life expectancy, and candidate for curative treatment. We performed a scoping revi...

Comparison of Pathologist and Artificial Intelligence-based Grading for Prediction of Metastatic Outcomes After Radical Prostatectomy.

European urology oncology
Gleason grade group (GG) is the most powerful prognostic variable in localized prostate cancer; however, interobserver variability remains a challenge. Artificial intelligence algorithms applied to histopathologic images standardize grading, but most...

Time-dependent personalized prognostic analysis by machine learning in biochemical recurrence after radical prostatectomy: a retrospective cohort study.

BMC cancer
BACKGROUND: For biochemical recurrence following radical prostatectomy for prostate cancer, treatments such as radiation therapy and androgen deprivation therapy are administered. To diagnose postoperative recurrence as early as possible and to inter...

Artificial intelligence in robot-assisted radical prostatectomy: where do we stand today?

Journal of robotic surgery
BACKGROUND: The development of Artificial Intelligence (AI) is one of the most revolutionary changes in modern history. The combination of AI and Robotic surgery can be used positively for better patient outcomes.

Application of deep learning for semantic segmentation in robotic prostatectomy: Comparison of convolutional neural networks and visual transformers.

Investigative and clinical urology
PURPOSE: Semantic segmentation is a fundamental part of the surgical application of deep learning. Traditionally, segmentation in vision tasks has been performed using convolutional neural networks (CNNs), but the transformer architecture has recentl...

Stress testing deep learning models for prostate cancer detection on biopsies and surgical specimens.

The Journal of pathology
The presence, location, and extent of prostate cancer is assessed by pathologists using H&E-stained tissue slides. Machine learning approaches can accomplish these tasks for both biopsies and radical prostatectomies. Deep learning approaches using co...

Deep learning prediction of error and skill in robotic prostatectomy suturing.

Surgical endoscopy
BACKGROUND: Manual objective assessment of skill and errors in minimally invasive surgery have been validated with correlation to surgical expertise and patient outcomes. However, assessment and error annotation can be subjective and are time-consumi...