Prostate Cancer

Inflammatory protein profiling in immune cells identifies molecular signatures for enhanced diagnostic precision in psoriatic arthritis.

Psoriatic arthritis (PsA) lacks reliable biomarkers to support early diagnosis and disease stratification. This study aimed to identify protein signatures associated with PsA and develop a clinically relevant model integrating molecular and clinical features. We conducted a cross-sectional study including 143 patients with PsA and 101 controls across three cohorts. The exploratory cohort included ...

AI-based modeling of treatment decisions in benign prostatic hyperplasia: a transformer-based comparative study.

Benign Prostatic Hyperplasia (BPH) is a common condition among aging men that often causes significant urinary symptoms, impacting their quality of life. This study employs advanced LLMs and deep learning models to predict whether BPH patients were managed with TURP or continued medical therapy using historical clinical data. We utilized a dataset of 883 patient cases from Jordan University Hospit...

Unsupervised clustering analysis unravels the role of systemic inflammatory indices in the prognosis of patients with locally advanced cervical cancer treated with chemoradiation.

BACKGROUND AND PURPOSE: This study aimed to predict the treatment outcomes and survival of patients with locally advanced cervical cancer (LACC) recei...

Language-Related Functional Connectivity in Post-Stroke Aphasia: Preliminary Findings from a Graph-Theoretical and Interpretable Machine Learning Study.

PURPOSE: To have an insight into language-related functional connectivity in post-stroke aphasia (PSA) from graph theory measurements when performing ...

PSA-1DCNN: Multimodal Biomarker and Text Integration for Lung Cancer Diagnosis.

Integrating multimodal data, such as unstructured clinical narratives and quantitative blood biomarkers, remains a major challenge in modern healthcar...

The influence of age and the presence of prostate cancer on prostate volume, PSA and PSA density.

OBJECTIVE: To assess prostate volume (PV) changes with age in symptomatic and asymptomatic men with and without clinically significant prostate cancer...

Accelerating Screening of Phase Separation Agents for Carbon Dioxide Capture: A Machine-Learning Framework with Interpretable Quantum Chemical Insights.

Against the backdrop of addressing climate change and reducing carbon emissions, carbon dioxide capture technology has gained increasing significance ...

Analysing DCE-MRI scans using hybrid techniques for early detection of prostate cancer based on fusion features of handcrafted and deep learning features.

Prostate cancer is among the most diagnosed malignancies in men worldwide and a leading cause of cancer-related mortality. Early and accurate diagnosi...

ERBB2 as a Prognostic Biomarker in Prostate Cancer: Integration of Single-Cell Transcriptomics, Deep Learning, and Immunohistochemical Validation.

Biochemical recurrence (BCR) is a critical factor affecting the prognosis of prostate cancer (PCa) patients, while T cell exhaustion and metastatic pr...

Artificial intelligence-derived transition zone PSA density as a triage tool to reduce unnecessary prostate systematic biopsies in MRI-negative men.

OBJECTIVES: The study aimed to assess the predictive performance of transition zone PSA density (TZ-PSAD) compared to conventional PSA density (PSAD) ...

EXPRESS: Convolutional Autoencoder for Automated Pre-Processing of Tumor Cell and Tissue Raman Spectra.

Raman spectroscopy (RS) is a label-free, non-destructive optical modality that provides a detailed profile of the molecular composition of a sample. T...

Predicting Treatment Outcomes in Patients With Psoriatic Arthritis or Axial Spondyloarthritis: An Artificial Intelligence-Driven Approach.

OBJECTIVE: To develop machine learning (ML) models to predict the probability at baseline of achieving low disease activity (LDA) and high health-rela...

Slice-prompted HR-CTV interactive segmentation for cervical cancer brachytherapy: A multi-center study.

BACKGROUND: In computed tomography (CT)-guided cervical cancer brachytherapy, the manual contouring for the high-risk clinical target volume (HR-CTV) ...

Machine learning model for fast prediction and uncertainty quantification of needle deflection during prostate biopsy.

BACKGROUND: Accurate needle placement is essential for prostate biopsy. Recently, transperineal prostate biopsies are receiving renewed interest due t...

From prostate-specific antigen to precision: The future of prostate cancer diagnosis with artificial intelligence, biomarkers, and imaging.

BACKGROUND: Prostate cancer (PCa) diagnosis has historically relied on prostate-specific antigen (PSA) testing. Although PSA screening significantly r...

Towards robust deep learning-based autosegmentation in MRI-planned gynecological brachytherapy: Importance of scalable development and comprehensive evaluation.

PURPOSE: To present comprehensive development and evaluation methodologies for a generalizable deep learning (DL)-driven autocontouring model of stand...

3D transformer-based dose prediction in HDR brachytherapy for cervical cancer.

An old disease, a new linguistic challenge for large language models: patient education on psoriasis and psoriatic arthritis in an underrepresented medical language.

OBJECTIVE: Large Language Models (LLMs) are increasingly applied to patient education, yet their performance in languages that are relatively underrep...

The role of focal therapy for localized prostate cancer: From diagnosis to ablation.

INTRODUCTION: Focal therapy (FT) has emerged as an intermediate therapeutic strategy between active surveillance (AS) and radical treatments for the m...

Artificial intelligence in diagnostic, prognostic, and predictive genomic biomarkers for prostate cancer: Ready for prime time?

INTRODUCTION: Until recently, the widespread use of genetic markers in prostate cancer (PCa) has been limited by the complexities and cost of genomic ...