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Prostatic Neoplasms

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Prognostic Importance of Lymphovascular Invasion for Specific Subgroup of Patients with Prostate Cancer After Robot-Assisted Radical Prostatectomy (The MSUG94 Group).

Annals of surgical oncology
OBJECTIVE: This study aimed to investigate whether lymphovascular invasion (LVI) was associated with oncological outcomes in patients with prostate cancer (PCa) undergoing robotic-assisted radical prostatectomy (RARP).

MicroSegNet: A deep learning approach for prostate segmentation on micro-ultrasound images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Micro-ultrasound (micro-US) is a novel 29-MHz ultrasound technique that provides 3-4 times higher resolution than traditional ultrasound, potentially enabling low-cost, accurate diagnosis of prostate cancer. Accurate prostate segmentation is crucial ...

The bladder neck preservation in robot assisted radical prostatectomy: Surgical and pathological outcome.

Archivio italiano di urologia, andrologia : organo ufficiale [di] Societa italiana di ecografia urologica e nefrologica
INTRODUCTION: The post-prostatectomy incontinence is influenced by multiple elements, anatomic components and biological factors. The bladder neck preservation, more accurate during robot assisted radical prostatectomy, works on two anatomic componen...

Treatment prediction with machine learning in prostate cancer patients.

Computer methods in biomechanics and biomedical engineering
There are various treatment modalities for prostate cancer, which has a high incidence. In this study, it is aimed to make predictions with machine learning in order to determine the optimal treatment option for prostate cancer patients. The study in...

Identifying multi-target drugs for prostate cancer using machine learning-assisted transcriptomic analysis.

Journal of biomolecular structure & dynamics
Prostate cancer is a leading cause of cancer death in men, and the development of effective treatments is of great importance. This study explored to identify the candidate drugs for prostate cancer by transcriptomic data and CMap database analysis. ...

Stimulated Raman Histology Interpretation by Artificial Intelligence Provides Near-Real-Time Pathologic Feedback for Unprocessed Prostate Biopsies.

The Journal of urology
PURPOSE: Stimulated Raman histology is an innovative technology that generates real-time, high-resolution microscopic images of unprocessed tissue, significantly reducing prostate biopsy interpretation time. This study aims to evaluate the ability fo...

ARCHERY: a prospective observational study of artificial intelligence-based radiotherapy treatment planning for cervical, head and neck and prostate cancer - study protocol.

BMJ open
INTRODUCTION: Fifty per cent of patients with cancer require radiotherapy during their disease course, however, only 10%-40% of patients in low-income and middle-income countries (LMICs) have access to it. A shortfall in specialised workforce has bee...

Clinical evaluation of deep learning and atlas-based auto-segmentation for organs at risk delineation.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Manual delineation of organs at risk and clinical target volumes is essential in radiotherapy planning. Atlas-based auto-segmentation (ABAS) algorithms have become available and been shown to provide accurate contouring for various anatomical sites. ...

Prospective effects of an artificial intelligence-based computer-aided detection system for prostate imaging on routine workflow and radiologists' outcomes.

European journal of radiology
OBJECTIVES: Artificial intelligence (AI) is expected to alleviate the negative consequences of rising case numbers for radiologists. Currently, systematic evaluations of the impact of AI solutions in real-world radiological practice are missing. Our ...

Deep learning-based whole-body characterization of prostate cancer lesions on [Ga]Ga-PSMA-11 PET/CT in patients with post-prostatectomy recurrence.

European journal of nuclear medicine and molecular imaging
PURPOSE: The automatic segmentation and detection of prostate cancer (PC) lesions throughout the body are extremely challenging due to the lesions' complexity and variability in appearance, shape, and location. In this study, we investigated the perf...