BACKGROUND: The global burden of ischaemic stroke (IS) is high, which is potentially relevant to stress hyperglycemia ratio (SHR) and glycaemic variability (GV). This study aims to evaluate the combined effect of the SHR and GV with predict short-ter...
BACKGROUND: Cell-free DNA is a promising source of biomarkers for early cancer detection and carries tumor-driven methylation and fragmentation features that have achieved good diagnostic efficacy across various cancers. However, there were no studie...
BACKGROUND: To construct and validate an optimal machine learning (ML)-based clinical-radiomics model integrating clinical and radiomics features for predicting recurrence risk within 2 years after radical surgery in patients with sinonasal squamous ...
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...
BACKGROUND: Inflammation plays a critical role in ischemic stroke (IS). This study aimed to identify inflammation-related genes and explore potential pharmacological agents for future preclinical validation in IS.
Plasmodium vivax is a malaria parasite with a broad geographic distribution worldwide. The unique biological characteristics of P. vivax, such as early gametocytogenesis and its latent hypnozoite stage, make it more difficult to control compared to P...
Accurate and efficient disease diagnosis remains a critical challenge in the healthcare sector. With the growing availability of biomedical data, machine learning techniques have become invaluable tools for developing intelligent disease detection sy...
Machine learning models are powerful tools for cardiovascular disease (CVD) prediction, but their performance is often limited by dataset size and class imbalance. While data augmentation techniques can address these issues, their impact on model int...
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 ...
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