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...
Brain age prediction based on anatomical MRI scans, as an essentially new measure in neuroimaging and aging research, provides a crucial marker for the early diagnosis of neurodegenerative diseases, cognitive health appraisal, and biological age pred...
Precancerous tongue lesion is a prevalent, complex, and highly perilous kind of cancer. The tumour might be in the salivary glands, tonsils, neck, cheek, and mouth. Oral Cancer (OC) is commonly identified in advanced stages due to the limited accurac...
The environmental pollutant Benzo[a]pyrene (B[a]P) and its ultimate metabolite B[a]P-7,8-diol-9,10-epoxide (BPDE) exhibit neurotoxic effects, yet the underlying molecular mechanisms remain enigmatic. Recently, ferroptosis has emerged as a potential p...
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...
Developmental psychology and affective computing have placed great emphasis on identifying children's emotional cues in recent times. In this study, a novel Spatio-Temporal Multimodal Emotion Recognition Network (ST-MERN) for child emotion classifica...
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 ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.