AIMC Topic: Prostatectomy
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Development of a deep learning system for predicting biochemical recurrence in prostate cancer.
BMC cancer
Feb 10, 2025
BACKGROUND: Biochemical recurrence (BCR) occurs in 20%-40% of men with prostate cancer (PCa) who undergo radical prostatectomy. Predicting which patients will experience BCR in advance helps in formulating more targeted prostatectomy procedures. Howe...
An Artificial Intelligence-Digital Pathology Algorithm Predicts Survival After Radical Prostatectomy From the Prostate, Lung, Colorectal, and Ovarian Cancer Trial.
The Journal of urology
Jan 22, 2025
PURPOSE: Clinical variables alone have limited ability to determine which patients will have recurrence after radical prostatectomy (RP). We evaluated the ability of locked multimodal artificial intelligence (MMAI) algorithms trained on prostate biop...
Deep Learning for Predicting Difficulty in Radical Prostatectomy: A Novel Evaluation Scheme.
Urology
Jan 13, 2025
OBJECTIVE: To explore new metrics for assessing radical prostatectomy difficulty through a two-stage deep learning method from preoperative magnetic resonance imaging.
Stimulated Raman Histology and Artificial Intelligence Provide Near Real-Time Interpretation of Radical Prostatectomy Surgical Margins.
The Journal of urology
Dec 17, 2024
PURPOSE: Balancing surgical margins and functional outcomes is crucial during radical prostatectomy for prostate cancer. Stimulated Raman histology (SRH) is a novel, real-time imaging technique that provides histologic images of fresh, unprocessed, a...
Stress testing deep learning models for prostate cancer detection on biopsies and surgical specimens.
The Journal of pathology
Dec 11, 2024
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...
Time-dependent personalized prognostic analysis by machine learning in biochemical recurrence after radical prostatectomy: a retrospective cohort study.
BMC cancer
Nov 25, 2024
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...
Development and Assessment of an AI-based Machine Learning Model for Predicting Urinary Continence and Erectile Function Recovery after Robotic-Assisted Radical Prostatectomy: Insights from a Prostate Cancer Referral Center.
Computer methods and programs in biomedicine
Nov 20, 2024
INTRODUCTION: Prostate cancer remains a significant health concern, with radical prostatectomy being a common treatment approach. However, predicting postoperative functional outcomes, particularly urinary continence and erectile function, poses chal...
Artificial intelligence in robot-assisted radical prostatectomy: where do we stand today?
Journal of robotic surgery
Nov 11, 2024
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.
Deep learning prediction of error and skill in robotic prostatectomy suturing.
Surgical endoscopy
Oct 21, 2024
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...
A Machine Learning Approach for Predicting Biochemical Outcome After PSMA-PET-Guided Salvage Radiotherapy in Recurrent Prostate Cancer After Radical Prostatectomy: Retrospective Study.
JMIR cancer
Sep 20, 2024
BACKGROUND: Salvage radiation therapy (sRT) is often the sole curative option in patients with biochemical recurrence after radical prostatectomy. After sRT, we developed and validated a nomogram to predict freedom from biochemical failure.
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