BACKGROUND: Depression is highly recurrent and heterogeneous. The unobtrusive, continuous collection of mobile sensing data via smartphones and wearable devices offers a promising approach to monitor and predict individual depression trajectories, di...
The relationship between interleukin-22 and clinical characteristics of patients with inflammatory bowel disease is uncertain. We sought to determine whether plasma interleukin-22 concentrations are associated with disease activity in a large populat...
COVID-19 has posed a significant global health challenge, affecting individuals across all age groups. While extensive research has focused on adults, pediatric patients exhibit distinct clinical characteristics that necessitate specialized predictiv...
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,...
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...
Chest X-ray (CXR) imaging plays a pivotal role in the diagnosis and prognosis of viral pneumonia. However, distinguishing COVID-19 CXRs from other viral infections remains challenging due to highly similar radiographic features. Most existing deep le...
BMC medical informatics and decision making
Jul 28, 2025
INTRODUCTION: Emergency departments (EDs) are critical for ensuring timely patient care, especially in triage, where accurate prioritisation is essential for patient safety and resource utilisation. Building on previous research, this study leverages...
Mild cognitive impairment (MCI) and dementia pose significant health challenges in aging societies, emphasizing the need for accessible, cost-effective, and noninvasive diagnostic tools. Electroencephalography (EEG) is a promising biomarker, but trad...
This study evaluates the performance of a machine learning model in classifying glaucoma severity using color fundus photographs. Glaucoma severity grading was based on the Hodapp-Parrish-Anderson (HPA) criteria incorporating the mean deviation value...
The Nancy histological index (NHI) is a measure of disease activity within colorectal biopsies and a predictor of clinical outcome in ulcerative colitis (UC). We measured interobserver agreement (IOA) during NHI scoring of 20 colorectal biopsies in U...
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