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Segmentation of Structural Components of Atherosclerotic Plaques on OCT Images Using Deep Machine Learning.

Kardiologiia
Aim        To develop an optimal method for automated segmentation of atherosclerotic plaque structural components in optical coherence tomography (OCT) images using an ensemble of deep learning neural network models based on a comparison of nine art...

Digital Twins for Monitoring Neuromotor Development in Preterm Infants: Conceptual Framework and Proof-of-concept Study.

Journal of medical systems
Preterm birth leads to an increased risk of long-term consequences, with over 50% of children born <30 weeks facing motor, cognitive, or behavioural impairments. Early monitoring of motor developmental trajectories, strongly associated with neurodeve...

Advancing Cell Therapy to Enhance Passive Avoidance Memory: Integrative Approaches Combining Neural-Like Cells and Rosmarinic Acid Through Behavioral, Molecular, and Histological Analyses.

Neurochemical research
Alzheimer's disease (AD) is characterized by progressive neurodegeneration, synaptic dysfunction, and cognitive decline. Regenerative strategies aim to replace lost neurons and modulate the inflammatory milieu to restore neural networks. This study e...

Heterogeneity of human insular cortex: five principles of functional organization across multiple cognitive domains.

Brain structure & function
The insular cortex serves as a critical hub for human cognition, but how its anatomically distinct subregions coordinate diverse cognitive, emotional, and social functions remains unclear. Using the Human Connectome Project's multi-task fMRI dataset ...

Identifying and predicting dietary patterns in the Dutch population using machine learning.

European journal of nutrition
PURPOSE: Nutritional epidemiological research is shifting its focus from individual nutrients to dietary patterns, which challenges traditional statistical methods. Here, we aim to apply various machine learning algorithms to identify and predict die...

Cardiovascular risk prediction in diabetes: a hybrid machine learning approach.

Biomedical physics & engineering express
Cardiovascular disease (CVD) is a major cause of morbidity and mortality in diabetic populations. Early detection of cardiovascular risk in diabetes is crucial to reduce complications, particularly in resource-limited settings. This study aimed to de...

Single-cell analysis of oxidative phosphorylation protein expression in pancreatic islets in type 2 diabetes.

The Journal of endocrinology
Mitochondrial dysfunction is a key feature of type 2 diabetes and is closely linked to ageing, a major risk factor for the disease. This study investigated islet cell composition and mitochondrial oxidative phosphorylation protein expression in pancr...

Intelligent sensory technologies, NIR spectroscopy and chemometrics combined with machine learning based on multi-source data fusion for comprehensive evaluation of Sinapis Semen in different processing degrees.

Journal of pharmaceutical and biomedical analysis
Sinapis Semen, as a traditional Chinese medicine, has an unclear relationship between its stir-frying degrees and sensory characteristics. Therefore, it is essential to develop a multi-index evaluation method to classify the processing degree of Sina...

Personalized real-time inference of momentary excitability from human EEG.

NeuroImage
The efficacy of transcranial magnetic stimulation (TMS) is often limited by non-adaptive protocols that disregard instantaneous brain states, potentially constraining therapeutic outcomes. Current EEG-guided approaches are hindered by their reliance ...

Multimodal integration of plasma biomarkers, MRI, and genetic risk to predict cerebral amyloid burden in Alzheimer's disease.

NeuroImage
Alzheimer's disease (AD), the most prevalent neurodegenerative disorder, is marked by the accumulation of amyloid-β (Aβ) plaques. Although cerebral Aβ positron emission tomography (Aβ-PET) remains the gold standard for assessing cerebral Aβ burden, i...