AIMC Topic: Prostatic Neoplasms
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Enhancing synthetic pelvic CT generation from CBCT using vision transformer with adaptive fourier neural operators.
Biomedical physics & engineering express
Aug 11, 2025
This study introduces a novel approach to improve Cone Beam CT (CBCT) image quality by developing a synthetic CT (sCT) generation method using CycleGAN with a Vision Transformer (ViT) and an Adaptive Fourier Neural Operator (AFNO).A dataset of 20 pro...
Diagnostic systematic review and meta-analysis of machine learning in predicting biochemical recurrence of prostate cancer.
Scientific reports
Aug 4, 2025
Prostate cancer (PCa) is the most prevalent malignant tumor in males, and many patients remain at risk of biochemical recurrence (BCR) following initial treatment. Accurate prediction of BCR is vital for effective clinical management and treatment pl...
The dosimetric impacts of ct-based deep learning autocontouring algorithm for prostate cancer radiotherapy planning dosimetric accuracy of DirectORGANS.
BMC urology
Aug 2, 2025
PURPOSE: In study, we aimed to dosimetrically evaluate the usability of a new generation autocontouring algorithm (DirectORGANS) that automatically identifies organs and contours them directly in the computed tomography (CT) simulator before creating...
AI generated annotations for Breast, Brain, Liver, Lungs, and Prostate cancer collections in the National Cancer Institute Imaging Data Commons.
Scientific data
Jul 29, 2025
The Artificial Intelligence in Medical Imaging (AIMI) initiative aims to enhance the National Cancer Institute's (NCI) Image Data Commons (IDC) by releasing fully reproducible nnU-Net models, along with AI-assisted segmentation for cancer radiology i...
Unveiling key pathomic features for automated diagnosis and Gleason grade estimation in prostate cancer.
BMC medical imaging
Jul 28, 2025
BACKGROUND: Recent advances in histology scanning technology and Artificial Intelligence (AI) offer great opportunities to support cancer diagnosis. The inability to interpret the extracted features and model predictions is one of the major issues li...
Automated radiotherapy treatment planning guided by GPT-4Vision.
Physics in medicine and biology
Jul 24, 2025
. Radiotherapy treatment planning is a time-consuming and potentially subjective process that requires iterative adjustment of model parameters to balance multiple conflicting objectives. Recent advancements in frontier artificial intelligence (AI) m...
Using machine learning to discover DNA metabolism biomarkers that direct prostate cancer treatment.
Scientific reports
Jul 18, 2025
DNA metabolism genes play pivotal roles in the regulation of cellular processes that contribute to cancer progression, immune modulation, and therapeutic response in prostate cancer (PC). Understanding the mechanisms by which these genes influence th...
Artificial intelligence in prostate cancer.
Chinese medical journal
Jul 9, 2025
Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial...
Development and retrospective validation of an artificial intelligence system for diagnostic assessment of prostate biopsies: study protocol.
BMJ open
Jul 7, 2025
INTRODUCTION: Histopathological evaluation of prostate biopsies using the Gleason scoring system is critical for prostate cancer diagnosis and treatment selection. However, grading variability among pathologists can lead to inconsistent assessments, ...
Performance of GPT-4 for automated prostate biopsy decision-making based on mpMRI: a multi-center evidence study.
Military Medical Research
Jul 7, 2025
BACKGROUND: Multiparametric magnetic resonance imaging (mpMRI) has significantly advanced prostate cancer (PCa) detection, yet decisions on invasive biopsy with moderate prostate imaging reporting and data system (PI-RADS) scores remain ambiguous.
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