Deep learning for microbiome analysis has shown potential for understanding microbial communities and human phenotypes. Here, we propose an approach, Transformer-based Robust Principal Component Analysis(TRPCA), which leverages the strengths of trans...
Traditional diagnostic methods for asthma, a widespread chronic respiratory illness, are often limited by factors such as patient cooperation with spirometry. Non-invasive acoustic analysis using machine learning offers a promising alternative for ob...
Decoding of continuous speech from electroencephalography (EEG) presents a promising avenue for understanding neural mechanisms of auditory processing and developing applications in hearing diagnostics. Recent advances in deep learning have improved ...
Trait emotional intelligence (EI) describes an individual's ability to control their emotions. In Chinese calligraphy, there is a saying that "the character reflects the person." This raises a hypothesis: is it possible to predict a writer's trait EI...
BACKGROUND: The potential for generative artificial intelligence (GenAI) to assist with clinical tasks is the subject of ongoing debate within biomedical informatics and related fields.
BACKGROUND: Hepatic encephalopathy (HE) contributes significantly to mortality among patients with liver cirrhosis. Early prediction of HE is essential for clinical decision-making, yet remains challenging-particularly in noncancer-related cirrhosis ...
BACKGROUND: The assessment of osteonecrosis of the femoral head (ONFH) often presents challenges in accuracy and efficiency. Traditional methods rely on imaging studies and clinical judgment, prompting the need for advanced approaches. This study aim...
Brain insulin action plays an important role in metabolic and cognitive health, but there is no biomarker available to assess brain insulin resistance in humans. Here, we developed a machine learning framework based on blood DNA methylation profiles ...
BACKGROUND: Digital interventions for mental health are pivotal for addressing barriers such as stigma, cost, and accessibility, particularly for underserved populations. While the effectiveness of digital interventions has been established, poor adh...
The numbers of robots in organizations grow at an increasing rate. However, very little is known about how robotization (i.e., the implementation of robots at work) affects the work characteristics of the jobs it impacts. This qualitative study focus...
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