Questions remain about how best to focus surveillance efforts for COVID-19 and other emerging respiratory diseases. We used an archive of COVID-19 data in Colorado from October 2020 to March 2024 to reconstruct seven real-time surveillance indicators...
Remote Patient Monitoring Systems (RPMS) are vital for tracking patients' health outside clinical settings, such as at home or in long-term care facilities. Wearable sensors play a crucial role in these systems by continuously collecting and transmit...
The emergence of large language models (LLMs) opens new horizons to leverage, often unused, information in clinical text. Our study aims to capitalise on this new potential. Specifically, we examine the utility of text embeddings generated by LLMs in...
Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are a growing global health concern, especially among the elderly, posing significant challenges to well-being and survival. GSK3β, a serine/threonine...
Multi-modal and multi-view imaging is essential for diagnosis and assessment of cervical spondylosis. Deep learning has increasingly been developed to assist in diagnosis and assessment, which can help improve clinical management and provide new idea...
Given artificial intelligence's transformative effects, studying safety is important to ensure it is implemented in a beneficial way. Convolutional neural networks are used in radiology research for prediction but can be corrupted through adversarial...
Altered gut metabolites are important for the inflammatory progression in children with NAFLD. Fecal and plasma samples were collected from 145 subjects including 53 non-alcoholic fatty liver (NAFL), 39 nonalcoholic steatohepatitis (NASH) and 53 obes...
Stress is widely acknowledged as a significant contributor to health issues. Recognizing stress involves assessing an individual's physiological and psychological responses to stressors, which is crucial for human well-being. Physiological signal-bas...
Machine learning models often rely on simple spurious features - patterns in training data that correlate with targets but are not causally related to them, like image backgrounds in foreground classification. This reliance typically leads to imbalan...
During cell-cell communication (CCC), pathways activated by different ligand-receptor pairs may have crosstalk with each other. While multiple methods have been developed to infer CCC networks and their downstream response using single-cell RNA-seq d...
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