AIMC Topic: Prostatic Neoplasms

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Applications of artificial intelligence in prostate cancer histopathology.

Urologic oncology
The diagnosis of prostate cancer (PCa) depends on the evaluation of core needle biopsies by trained pathologists. Artificial intelligence (AI) derived models have been created to address the challenges posed by pathologists' increasing workload, work...

Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images.

Journal of the American Society for Mass Spectrometry
Prostate cancer is one of the most common cancers globally and is the second most common cancer in the male population in the US. Here we develop a study based on correlating the hematoxylin and eosin (H&E)-stained biopsy data with MALDI mass-spectro...

Sustainable functional urethral reconstruction improves early urinary continence after robot-assisted radical prostatectomy: a randomised controlled trial.

BJU international
OBJECTIVE: To evaluate the impact of sustainable functional urethral reconstruction (SFUR) on early recovery of urinary continence (UC) after robot-assisted radical prostatectomy.

Feasibility, Safety, and Functional Outcomes of Pelvic Hypothermia Induced Using a Rectal Cooling Device During Robot-Assisted Radical Prostatectomy: A Phase I/II Trial.

Journal of endourology
Radical prostatectomy (RP) is one of the standard treatments for localized prostate cancer. However, in terms of functional outcomes, there are aspects that still need improvements. We designed this prospective phase I/II clinical trial to assess th...

Differential diagnosis of prostate cancer and benign prostatic hyperplasia based on DCE-MRI using bi-directional CLSTM deep learning and radiomics.

Medical & biological engineering & computing
Dynamic contrast-enhanced MRI (DCE-MRI) is routinely included in the prostate MRI protocol for a long time; its role has been questioned. It provides rich spatial and temporal information. However, the contained information cannot be fully extracted ...

Radiomic-based machine learning model for the accurate prediction of prostate cancer risk stratification.

The British journal of radiology
OBJECTIVES: To precisely predict prostate cancer (PCa) risk stratification, we constructed a machine learning (ML) model based on magnetic resonance imaging (MRI) radiomic features.

Computer-aided diagnosis in prostate cancer: a retrospective evaluation of the Watson Elementary system for preoperative tumor characterization in patients treated with robot-assisted radical prostatectomy.

World journal of urology
PURPOSE: Computer-aided diagnosis (CAD) may improve prostate cancer (PCa) detection and support multiparametric magnetic resonance imaging (mpMRI) readers for better characterization. We evaluated Watson Elementary (WE) CAD system results referring t...

Prostate cancer malignancy detection and localization from mpMRI using auto-deep learning as one step closer to clinical utilization.

Scientific reports
Automatic diagnosis of malignant prostate cancer patients from mpMRI has been studied heavily in the past years. Model interpretation and domain drift have been the main road blocks for clinical utilization. As an extension from our previous work we ...

Comparison of therapeutic features and oncologic outcome in patients with pN1 prostate cancer among robot-assisted, laparoscopic, or open radical prostatectomy.

International journal of clinical oncology
OBJECTIVES: To compare the therapeutic features and oncological outcomes of robot-assisted radical prostatectomy (RARP) with those of open radical prostatectomy (ORP) or laparoscopic radical prostatectomy (LRP) in lymph node (LN) positive prostate ca...