Face recognition based on deep neural networks has achieved great success, but its application in resource-constrained and unconstrained scenarios, such as vehicle images from traffic monitoring systems, remains challenging. These scenarios involve c...
The longitudinal course of epilepsy remains largely unpredictable. This study aimed to predict final outcome and classify dynamic longitudinal trajectories using artificial intelligence. A total of 2586 patients who first visited our epilepsy special...
To address the long-standing challenges children with autism face in social skills and emotional regulation, this study introduces Emotion-based Music Intelligent Network (EmoMusik-Net)-a deep learning model designed for intelligent music therapy. Th...
Heart attacks remain a major cause of morbidity and mortality, particularly among middle-aged and older adults, often aggravated by unhealthy lifestyles and limited preventive care. Early identification and prioritization of at-risk individuals are e...
Accurately predicting human perception of tactile roughness remains challenging because previous models often used limited mechanical properties, small sample sizes, and insufficient validation methods. To address these limitations, we developed a pr...
Primary vitreoretinal lymphoma (PVRL) is a rare and aggressive intraocular malignancy that is frequently misdiagnosed because of its nonspecific early manifestations and the lack of effective screening tools. We conduct a multicentre case-control stu...
The adoption of whole genome sequencing (WGS) in clinical oncology is challenged by low data quality and increased artifacts in standard-of-care formalin-fixed paraffin-embedded (FFPE) samples. Analysis of 56 fresh frozen (FF) and FFPE matched pairs ...
Multiplexed imaging has transformed our ability to study tissue organization by capturing thousands of cells and molecules in their native context. However, these datasets are enormous, often comprising tens of gigabytes per image, and require comple...
BACKGROUND: Preoperative endometrial cancer (EC) diagnosis often depends on radiologists' expertise, which introduces subjectivity. Recent studies have explored radiomics-based machine learning (ML) models for detecting myometrial invasion (MI), but ...
BACKGROUND: Virtual patient (VP) simulations can be used to practice clinical reasoning (CR) in controlled learning environments. Traditional computer-based VP platforms often lack the authenticity and interactivity required for effective CR training...
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