AIMC Topic: Prostatic Neoplasms

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Performance of Retrieval-Augmented Generation Large Language Models in Guideline-Concordant Prostate-Specific Antigen Testing: Comparative Study With Junior Clinicians.

Journal of medical Internet research
BACKGROUND: Prostate-specific antigen (PSA) testing remains the cornerstone of early prostate cancer detection. Society guidelines for prostate cancer screening via PSA testing serve to standardize patient care and are often used by trainees, junior ...

Using ChatGPT-4 for Lay Summarization in Prostate Cancer Research to Advance Patient-Centered Communication: Large-Scale Generative AI Performance Evaluation.

Journal of medical Internet research
BACKGROUND: The increasing volume and complexity of biomedical literature pose challenges for making scientific knowledge accessible to lay audiences. Lay summaries, now widely encouraged or required by journals, aim to bridge this gap by promoting h...

Revealing new associations between lncRNAs and diseases through cross attention mechanism and multiple level feature fusion.

Scientific reports
Revealing new lncRNA-disease associations (LDAs) is necessary to decipher pathological mechanisms and find new clues of diagnosis and therapy for complex diseases. However, experimental methods for LDA identification need a significant amount of time...

AI-driven software for automated quantification of skeletal metastases and treatment response evaluation using whole-body diffusion-weighted MRI (WB-DWI) in advanced prostate cancer.

Physics in medicine and biology
. Quantitative assessment of treatment response in advanced prostate cancer (APC) with bone metastases remains an unmet clinical need. Whole-body diffusion-weighted MRI (WB-DWI) provides two response biomarkers: total diffusion volume (TDV) and globa...

Label-free histological identification of intraductal carcinoma of the prostate using texture analysis-based multimodal stimulated Raman scattering microscopy.

Scientific reports
Intraductal carcinoma of the prostate (IDC-P) is a very aggressive histopathological subtype of prostate cancer (PCa) that is strongly associated with poor clinical outcomes but for which no accurate biomarkers exist. Here, we demonstrate a novel app...

Dual-arc VMAT machine parameter optimization for localized prostate cancer using deep reinforcement learning.

Physics in medicine and biology
To develop and evaluate a deep reinforcement learning (RL) framework for rapid and automatic machine parameter optimization of volumetric modulated arc therapy (VMAT) treatment plans for localized prostate cancer.A multi-task policy network combining...

Integrating multi-omics and machine learning to decipher the role of GSTP1 in endocrine-disrupting chemical-induced prostate cancer pathogenesis.

European journal of pharmacology
Prostate cancer (PCa) pathogenesis involves complex interactions between genetic susceptibility and exposure to endocrine-disrupting chemicals (EDCs). This study aimed to systematically identify key genes linking EDC exposure to PCa using an integrat...

Unveiling the role of harmonization on clinically significant prostate cancer detection using MRI.

Scientific reports
Accurate detection and classification of clinically significant prostate cancer remain critical challenges in medical imaging. Despite numerous studies focusing on feature extraction and classification, none have systematically assessed the impact of...

Interpretable weakly-supervised learning through kernel density matrices: A digital pathology use case.

PloS one
Classification methods based on deep learning require selecting between fully-supervised or weakly-supervised approaches, each presenting limitations in uncertainty quantification and interpretability. A framework unifying both supervision modes whil...

The relationship between the neutrophil percentage to albumin ratio and the occurrence of prostate cancer.

PloS one
BACKGROUND: Although prior research has indicated that nutritional and inflammatory markers may play a role in prostate cancer development, the exact interplay and underlying mechanisms are not yet fully understood.