BACKGROUND: Radiomics and artificial intelligence have shown strong predictive capabilities in urinary stone research, particularly concerning stone composition, characteristics, and treatment outcomes. However, the association of stone radiomics and...
Epstein-Barr virus (EBV) exacerbates inflammatory bowel disease (IBD) and is challenging to monitor with invasive or costly tests. We investigated whether explainable machine learning can predict EBV infection from routine clinical data in ulcerative...
Schizophrenia (SZ) is increasingly recognized as a network disorder marked by abnormal functional connectivity, yet the clinical utility of fMRI remains limited. Electroencephalography (EEG) provides a more practical alternative, though conventional ...
The role of chromatin regulators (CRs) in mediating epigenetic changes during tuberculosis (TB) infection remains poorly understood. This study aimed to determine the efficacy of CRs in diagnosing TB and characterizing its heterogeneity. GSE83456 dat...
This study analyzes university students' attitudes towards artificial intelligence. Within the scope of the research, the data obtained from 1379 students through scale application were classified into three classes as "Insufficient", "Sufficient" an...
This study investigates how passengers perceive ride safety and develop trust in Robotaxi services in the absence of human drivers, with a focus on differences between daytime and nighttime scenarios. Drawing on the Elaboration Likelihood Model (ELM)...
This study investigates how personality traits, specifically those measured by the HEXACO Personality Inventory and the Dark Triad, predict university students' attitudes toward generative artificial intelligence (GAI) and their engagement in GAI-rel...
To develop and validate a machine learning (ML) model for predicting early recurrence (ER) within two years post-surgery in non-small cell lung cancer (NSCLC) patients. This multicenter cohort study included 3,171 NSCLC patients who underwent radical...
BACKGROUND: Subjective report of pain remains the gold standard for assessing symptoms in patients with chronic pain and their response to analgesics. This subjectivity underscores the importance of understanding patients' personal narratives, as the...
BACKGROUND: Preventive strategies integrated with digital health and artificial intelligence (AI) have significant potential to mitigate the global burden of atherosclerotic cardiovascular disease (ASCVD). AI-enabled clinical decision support (CDS) s...
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