Deep learning (DL) has the potential to deliver significant clinical benefits. In recent years, an increasing number of DL-based systems have been approved by the relevant regulators, e.g. FDA. Although obtaining regulatory approvals is a prerequisit...
BACKGROUND AND PURPOSE: Data-driven decision-making in radiation oncology (RO) relies on integrating real-world data effectively. Synthetic data (SD), generated through machine learning, offers a solution by mimicking real-world data without compromi...
PURPOSE: To compare prostate cancer lesion detection using conventional and artificial intelligence (AI)-assisted image interpretation at multiparametric MRI (mpMRI).
Journal of the American Medical Informatics Association : JAMIA
Jun 1, 2025
OBJECTIVE: Diagnosis codes documented in electronic health records (EHR) are often relied upon to clinically phenotype patients for biomedical research. However, these diagnoses can be incomplete and inaccurate, leading to false negatives when search...
BACKGROUND: Diffusion-weighted imaging with higher b-value improves detection rate for prostate cancer lesions. However, obtaining high b-value DWI requires more advanced hardware and software configuration. Here we use a novel deep learning network,...
BACKGROUND: Generative artificial intelligence (AI) chatbots may be useful tools for supporting shared prostate cancer (PrCA) screening decisions, but the information produced by these tools sometimes lack quality or credibility. "Prostate Cancer Inf...
Artificial intelligence (AI) is becoming an integral part of pathological assessment and diagnostic procedures in modern pathology. As most prostate cancers (PCa) arise from glandular epithelial tissue, an AI-based methodology has been developed to r...
American journal of clinical pathology
May 17, 2025
OBJECTIVE: The highly specialized language used in prostate biopsy pathology reports coupled with low rates of health literacy leave some patients unable to comprehend their medical information. Patients' use of online search engines can lead to misi...
Studies in health technology and informatics
May 15, 2025
The ASCAPE project aims to improve the health-related quality of life of prostate cancer patients using artificial intelligence-driven solutions. This study tries to unravel the complex relationships between patient data variables and urinary inconti...
Studies in health technology and informatics
May 15, 2025
Prostate cancer is a leading cause of cancer-related deaths, with Gleason grading being key for assessing tumor aggressiveness. We propose a Graph Neural Network-based approach to automate Gleason grading using the Automated Gleason Grading Challenge...
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