Among numerous medical imaging modalities, ultrasound imaging is one of the most commonly used diagnostic methods in clinical practice. However, ultrasound diagnosis heavily relies on physician experience, and diagnostic results often lack reproducib... read more
OBJECTIVE: To develop a robust and compact deep learning model for automated knee cartilage segmentation on point-of-care ultrasound (POCUS) devices. METHODS: We propose MonoUNet, a novel, highly compact segmentation model consisting of (i) an aggres... read more
BACKGROUND: Knee osteoarthritis (OA) is a degenerative, progressive joint disease with narrowing of the joint space, formation of osteophytes, and sclerosis of the subchondral regions, which results in disability and loss of mobility and quality of l... read more
Metabolic disorders, including obesity, type 2 diabetes, metabolic syndrome, and fatty liver disease, reflect multifactorial interactions among diet, host genetics, the environment, and the gut microbiome. However, conventional population-level dieta... read more
Programmable materials are an emerging class of matter capable of dynamically altering their properties, structure, or function in response to external stimuli. While most research has treated chemical and mechanical responsiveness separately, integr... read more
Food research international (Ottawa, Ont.)
May 8, 2026
The global population is aging at an accelerating pace, and sarcopenia has emerged as a central challenge to elderly health. Food-derived bioactive peptides, as natural functional compounds, can interact significantly with the gut microbiota, thereby... read more
European heart journal. Digital health
May 8, 2026
AIMS: AI in electrocardiography (ECG) has diverged into two paths: traditional signal processing with machine learning, and deep learning of raw waveforms. The former preserves physiological interpretability but may miss novel patterns, while the lat... read more
International journal of medical informatics
May 8, 2026
BACKGROUND: Clinical decision algorithms used by clinicians guide evidence-based decisions and actions. Automated tools can help with the adoption and sustainability of these algorithms, and automation is especially needed in the emergency setting wh... read more
OBJECTIVES: To develop and externally validate a multicenter MRI-based machine learning model integrating intra-tumoral heterogeneity (ITH) index, conventional radiomics (C-radiomics) and clinical variables for predicting one-year pulmonary metastasi... read more
Marine oil spills are one of the most severe anthropogenic threats to oceanic ecosystems, coastal communities, and global economic stability. While traditional monitoring and response approaches have played a foundational role in oil spill management... read more
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