OBJECTIVE: To evaluate the agreement and repeatability of an automated robotic ultrasound system (ARTHUR V.2.0) combined with an AI model (DIANA V.2.0) in assessing synovial hypertrophy (SH) and Doppler activity in rheumatoid arthritis (RA) patients,...
BACKGROUND: Early assessment of mild cognitive impairment (MCI) in older adults is crucial, as it enables timely interventions and decision-making. In recent years, researchers have been exploring the potential of gamified interactive systems (GISs) ...
This study employed machine learning models to quantitatively analyze liver fat content from MRI images for the evaluation of liver fibrosis and disease severity in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). A total o...
BACKGROUND: Angina pectoris, a comparatively common complaint among older adults, is a critical warning sign of underlying coronary heart disease. We aimed to develop machine learning-based models using multiple algorithms to predict and identify the...
INTRODUCTION: Natural language processing (NLP) has been used to analyze unstructured imaging report data, yet its application in identifying chronic kidney disease (CKD) features from kidney ultrasound reports remains unexplored.
The clinical adenoma - carcinoma progression represents a well-established framework for understanding colorectal cancer (CRC) development, although the molecular mechanisms underlying this transition remain only partially understood. Increasing evid...
The length of stay (LOS) for patients in hospitals is crucial for workforce planning, resource allocation, and bed capacity management, impacting healthcare costs, future needs and financial planning. This study focuses on calculating the LOS for Chr...
PURPOSE: To evaluate the performance of artificial intelligence (AI)-based coronary artery calcium scoring (CACS) on non-electrocardiogram (ECG)-gated chest CT, using manual quantification as the reference standard, while characterizing per-vessel re...
BACKGROUND: Acute cholangitis (AC) presents with significant clinical heterogeneity, and existing severity classifications have limited prognostic value in critically ill patients. Subtypes of AC in critically ill patients have not been investigated.
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 4, 2025
PURPOSE: Accurate preoperative grading of gliomas is critical for therapeutic planning and prognostic evaluation. We developed a noninvasive machine learning model leveraging whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) b...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.