Prostate Cancer

Utility of the PROSTest, a Novel Blood-Based Molecular Assay, Versus PSA for Prostate Cancer Stratification and Detection of Disease.

BACKGROUND: Prostate cancer (PCa) is the most common solid organ cancer in men and the fifth leading cause of cancer-related deaths globally. PSA helps identify men at risk but has low specificity and has resulted in unnecessary biopsies. The PROSTest, a novel machine learning-based 27-gene mRNA liquid biopsy assay, was developed to detect PCa. We evaluated its utility as a stratification tool in ...

Virtual screening and experimental validation of small-molecule compounds targeting AR in prostate cancer.

Prostate cancer ranks as the second most prevalent malignancy among men, with its progression predominantly driven by androgen receptor (AR) signaling. Despite the centrality of androgen deprivation therapy (ADT) in managing advanced prostate cancer, the emergence of resistance culminating in castration-resistant prostate cancer (CRPC) remains a formidable challenge. In this study, an integrative ...

A hybrid decision support system using rule-based and AI methods: the OnCATs knowledge-based framework.

BACKGROUND AND SIGNIFICANCE: Clinical decision support systems (CDSS) can improve evidence-based oncology care, but many rely on opaque AI models that...

Development and validation of a nomogram combining PI-RADS v2.1 and clinical indicators for the diagnosis of prostate cancer in patients with PSA ≤ 20 ng/mL.

PURPOSE: This investigation focused on developing a predictive clinical tool that combines biparametric MRI-derived PI-RADS v2.1 assessments with pati...

Artificial Intelligence 3D Augmented Reality-guided Robotic Prostatectomy Versus Cognitive MRI Intervention: Results of the Prospective Randomized RIDERS Trial.

BACKGROUND AND OBJECTIVE: Three-dimensional (3D) augmented reality (AR) and artificial intelligence (AI) technologies have recently been introduced to...

Prostate MR image segmentation using a multi-stage network approach.

Prostate cancer (PCa) remains one of the most prevalent cancers among men, with over 1.4 million new cases and 375,304 deaths reported globally in 202...

High-throughput LDI MS technology decodes the distinct metabolic landscape of prostate cancer in a large-scale cohort.

BACKGROUND: Prostate cancer (PCa) remains a leading global malignancy, yet current diagnostic reliance on prostate-specific antigen (PSA) testing is l...

Interpretable machine learning models for survival prediction in prostate cancer bone metastases.

Prostate cancer bone metastasis (PCBM) is a highly lethal condition with limited survival. Accurate survival prediction is essential for managing thes...

Combining multi-parametric MRI radiomics features with tumor abnormal protein to construct a machine learning-based predictive model for prostate cancer.

This study aims to investigate the diagnostic value of integrating multi-parametric magnetic resonance imaging (mpMRI) radiomic features with tumor ab...

Non-conventional diagnostic tools for lower urinary tract symptoms and bladder outlet obstruction in men: a perspective review.

Introduction Assessing male lower urinary tract symptoms (LUTS) due to Benign outlet obstruction (BOO) remains a challenge in urology due to the limit...

Sex differences in serum proteomic profiles in psoriatic arthritis.

OBJECTIVES: Sex-related differences exist in the clinical presentation and treatment outcomes of patients with psoriatic arthritis (PsA). The biologic...

Prospective cohort study integrating plasma proteomics and machine learning for early risk prediction of prostate cancer.

BACKGROUND: Early detection of prostate cancer (PCa) remains a clinical challenge. Plasma proteomics provides a non-invasive tool for identifying indi...

PruEV-AI: a Simple Approach Combines Urinary Extracellular Vesicle Isolation with AI-Assisted Analysis for Prostate Cancer Diagnosis.

Urinary extracellular vesicles (uEVs) are a promising source of prostate-derived biomarkers for non-invasive prostate cancer (PCa) diagnosis. However,...

Deep learning-based applicator selection between Syed and T&O in high-dose-rate brachytherapy for locally advanced cervical cancer: a retrospective study.

High-dose-rate (HDR) brachytherapy is integral to the standard-of-care for locally advanced cervical cancer (LACC). Currently, selection of brachyther...

SPCF-YOLO: An Efficient Feature Optimization Model for Real-Time Lung Nodule Detection.

Accurate pulmonary nodule detection in CT imaging remains challenging due to fragmented feature integration in conventional deep learning models. This...

Using AI to triage patients without clinically significant prostate cancer using biparametric MRI and PSA.

OBJECTIVES: To train and evaluate the performance of a machine learning triaging tool that identifies MRI negative for clinically significant prostate...

Incorporating organ deformation in biological modeling and patient outcome study for permanent prostate brachytherapy.

Permanent prostate brachytherapy has inherent intraoperative organ deformation due to the inflatable trans-rectal ultrasound probe cover. Since the ma...

A novel network architecture for post-applicator placement CT auto-contouring in cervical cancer HDR brachytherapy.

BACKGROUND: High-dose-rate brachytherapy (HDR-BT) is an integral part of treatment for locally advanced cervical cancer, requiring accurate segmentati...

Combining Clinical, Genetic and Protein Markers Using Machine Learning Models Discriminates Psoriatic Arthritis Patients From Those With Psoriasis.

BACKGROUND: Psoriatic Arthritis (PsA), an immune mediated inflammatory arthritis, affects a quarter of patients with cutaneous psoriasis, usually afte...

Dual nanozyme sensor enables rapid at-home cancer surveillance.

Early detection of cancer is critical for improving patient survival rates, and current in vitro diagnostic methods show great potential, particularly...