BACKGROUND: Emergency department (ED) crowding is often attributed to a slow hospitalization process, leading to reduced quality of care. Predicting early disposition in patients presenting with cardiac issues is challenging: most are ultimately disc...
BACKGROUND: The development and introduction of an artificial intelligence (AI)-based clinical decision support system (CDSS) in surgical departments as part of the "Supporting Surgery with Geriatric Co-management and AI" project addresses the challe...
BACKGROUND: Accurate staging of esophageal cancer is crucial for determining prognosis and guiding treatment strategies, but manual interpretation of radiology reports by clinicians is prone to variability and limited accuracy, resulting in reduced s...
BACKGROUND: Artificial intelligence-assisted conversational agents have been applied and developed in outpatient departments to improve health services in China. However, there has been little research that evaluates the effect of artificial intellig...
BACKGROUND: Uncorrected refractive error affects approximately 19 million children globally, resulting in preventable vision loss. However, cycloplegic refraction, the gold standard for assessment, remains largely inaccessible in low-resource setting...
The canonical framework for testing pain and mechanical sensitivity in rodents is manual delivery of stimuli to the paw. However, this approach is time-consuming, produces variability in results, requires significant training, and is ergonomically un...
Echocardiographic left ventricular hypertrophy (Echo-LVH) is frequently underdetected by traditional electrocardiogram (ECG) criteria due to limited sensitivity. We investigated whether integrating ECG with vectorcardiography (VCG) using a clinically...
Visceral pleural invasion (VPI) is a critical prognostic factor in early-stage non-small-cell lung cancer (NSCLC), significantly affecting patient outcomes. Conventional computed tomography (CT) often fails to diagnose VPI accurately. This retrospect...
BACKGROUND: Depression exhibits significant heterogeneity in antidepressant treatment response. This study aimed to develop an Electroencephalography (EEG)-based machine learning model integrating multidimensional features to predict selective seroto...
BACKGROUND AND OBJECTIVES: High-dose methylprednisolone (MP) is the global standard for treating pregnancy-associated relapses in multiple sclerosis (MS). Given that glucocorticoids cross the placenta and may interfere with fetal brain development, c...
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