Latest AI and machine learning research in prostate cancer for healthcare professionals.
BACKGROUND: Multiple parameters including PSA, PSAD, and PIRADS v2.1 score, are being associated in an effort to increase the overall detection rate of clinically significant prostate cancer (csPCa). This study aims to explore gray zone PSA and PSAD correlated with PIRADS score in the detection of csPCa using MRI-US fusion prostate biopsy.
Despite the extensive use of biomarkers like PSA, AMACR, and PCA3, prostate cancer (PCa) is still a major clinical challenge, demanding the development of more precise and specific methods for diagnosis. In this study, a deep learning model was applied to identify ten key genes from a pool of 68 common differentially expressed genes in the three transcriptomic datasets. The model demonstrated high...
Glioblastoma (GBM) is a fatal brain cancer known for its rapid and aggressive growth, with some studies indicating that females may have better surviv...
Despite being one of the most prevalent cancers, prostate cancer (PCa) shows a significantly high survival rate, provided there is timely detection an...
PURPOSE: Minimally invasive needle-based interventions are commonly used in cancer diagnosis and treatment, including procedures, such as biopsy, brac...
BACKGROUND: The use of deep learning-based auto-contouring algorithms in various treatment planning services is increasingly common. There is a notabl...
PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lung cancer in practical clinical applications remain...
In the field of treatment and prevention of immune-related bone diseases, significant challenges persist, necessitating the urgent exploration of new ...
This study developed and evaluated an automatic segmentation model based on the Mamba framework (AM-UNet) for rapid and precise delineation of high-ri...
BACKGROUND: Machine learning (ML) is a significant area of artificial intelligence, which can improve the accuracy of predictive or diagnostic models ...
Automatic clinical tumor volume (CTV) delineation is pivotal to improving outcomes for interstitial brachytherapy cervical cancer. However, the promin...
Predicting blood-brain barrier (BBB) penetration is crucial for developing central nervous system (CNS) drugs, representing a significant hurdle in su...
OBJECTIVES: Develop an interpretable machine learning model to detect patients with newly diagnosed psoriatic arthritis (PsA) in a cohort of psoriasis...
The objective of this study was to employ machine learning to identify shared differentially expressed genes (DEGs) in prostate cancer (PCa) initiatio...
AIM: This review aims to evaluate the role of interventional radiotherapy (IRT - brachytherapy) in the clinical management of head and neck (H&N) canc...
In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and magnetic resonance imaging (MRI) enable early predic...
BACKGROUND: Proton pencil beam scanning (PBS) treatment planning for head and neck (H&N) cancers is a time-consuming and experience-demanding task whe...
PURPOSE: This study evaluates the feasibility of using robotic-assisted bronchoscopy with cone beam computed tomography (RB-CBCT) platform to perform ...
BACKGROUND: In this study, we attempted to select the optimum cases for a prostate biopsy based on routine laboratory test results in addition to pros...
PURPOSE: High dose rate (HDR) prostate brachytherapy (BT) procedure requires image-guided needle insertion. Given that general anesthesia is often emp...