AIMC Topic: Prostatic Neoplasms

Clear Filters Showing 281 to 290 of 1447 articles

Part I: prostate cancer detection, artificial intelligence for prostate cancer and how we measure diagnostic performance: a comprehensive review.

Current problems in diagnostic radiology
MRI has firmly established itself as a mainstay for the detection, staging and surveillance of prostate cancer. Despite its success, prostate MRI continues to suffer from poor inter-reader variability and a low positive predictive value. The recent e...

Explainable and visualizable machine learning models to predict biochemical recurrence of prostate cancer.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PURPOSE: Machine learning (ML) models presented an excellent performance in the prognosis prediction. However, the black box characteristic of ML models limited the clinical applications. Here, we aimed to establish explainable and visualizable ML mo...

Advantage of whole-mount histopathology in prostate cancer: current applications and future prospects.

BMC cancer
BACKGROUND: Whole-mount histopathology (WMH) has been a powerful tool to investigate the characteristics of prostate cancer. However, the latest advancement of WMH was yet under summarization. In this review, we offer a comprehensive exposition of cu...

LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations.

International journal of computer assisted radiology and surgery
PURPOSE: The standard of care for prostate cancer (PCa) diagnosis is the histopathological analysis of tissue samples obtained via transrectal ultrasound (TRUS) guided biopsy. Models built with deep neural networks (DNNs) hold the potential for direc...

An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate Cancer.

Journal of imaging informatics in medicine
Uptake segmentation and classification on PSMA PET/CT are important for automating whole-body tumor burden determinations. We developed and evaluated an automated deep learning (DL)-based framework that segments and classifies uptake on PSMA PET/CT. ...

Harnessing artificial intelligence for prostate cancer management.

Cell reports. Medicine
Prostate cancer (PCa) is a common malignancy in males. The pathology review of PCa is crucial for clinical decision-making, but traditional pathology review is labor intensive and subjective to some extent. Digital pathology and whole-slide imaging e...

Development and validation of an imageless machine-learning algorithm for the initial screening of prostate cancer.

The Prostate
PURPOSE: Prostate specific antigen (PSA) testing is a low-cost screening method for prostate cancer (PCa). However, its accuracy is limited. While progress is being made using medical imaging for PCa screening, PSA testing can still be improved as an...

Prostatic Fossa Pseudoaneurysm After Robot-Assisted Radical Prostatectomy (RARP): A Case Report.

The American journal of case reports
BACKGROUND RARP is an established procedure in treatment of localized prostate cancer. Hemorrhagic complications in the postoperative period are rare, but sometimes life-threatening. Adequate monitoring and prompt intervention in these unusual scenar...

Adequacy of prostate cancer prevention and screening recommendations provided by an artificial intelligence-powered large language model.

International urology and nephrology
PURPOSE: We aimed to assess the appropriateness of ChatGPT in providing answers related to prostate cancer (PCa) screening, comparing GPT-3.5 and GPT-4.