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TASA: Temporal Attention With Spatial Autoencoder Network for Odor-Induced Emotion Classification Using EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The olfactory system enables humans to smell different odors, which are closely related to emotions. The high temporal resolution and non-invasiveness of Electroencephalogram (EEG) make it suitable to objectively study human preferences for odors. Ef...

s-TBN: A New Neural Decoding Model to Identify Stimulus Categories From Brain Activity Patterns.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Neural decoding is still a challenging and a hot topic in neurocomputing science. Recently, many studies have shown that brain network patterns containing rich spatiotemporal structural information represent the brain's activation information under e...

Unlocking the full potential of mesenchymal stromal cell therapy for osteoarthritis through machine learning-based in silico trials.

Cytotherapy
Despite the potential of mesenchymal stromal cells (MSCs) in osteoarthritis (OA) treatment, the challenge lies in addressing their therapeutic inconsistency. Clinical trials revealed significantly varied therapeutic outcomes among patients receiving ...

Surveying haemoperfusion impact on COVID-19 from machine learning using Shapley values.

Inflammopharmacology
BACKGROUND: Haemoperfusion (HP) is an innovative extracorporeal therapy that utilizes special cartridges to filter the blood, effectively removing pro-inflammatory cytokines, toxins, and pathogens in COVID-19 patients. This retrospective cohort study...

Deploying Robot-Led Activities for People with Dementia at Aged Care Facilities: A Feasibility Study.

Journal of the American Medical Directors Association
OBJECTIVES: To explore the feasibility of deploying robot-led activities for people with dementia living in aged care facilities.

Using a clinical narrative-aware pre-trained language model for predicting emergency department patient disposition and unscheduled return visits.

Journal of biomedical informatics
The increasing prevalence of overcrowding in Emergency Departments (EDs) threatens the effective delivery of urgent healthcare. Mitigation strategies include the deployment of monitoring systems capable of tracking and managing patient disposition to...

Alzheimer's disease early screening and staged detection with plasma proteome using machine learning and convolutional neural network.

The European journal of neuroscience
Alzheimer's disease (AD) stands as the prevalent progressive neurodegenerative disease, precipitating cognitive impairment and even memory loss. Amyloid biomarkers have been extensively used in the diagnosis of AD. However, amyloid proteins offer lim...

Machine Learning-Based Mortality Prediction in Chronic Kidney Disease among Heart Failure Patients: Insights and Outcomes from the Jordanian Heart Failure Registry.

Medicina (Kaunas, Lithuania)
Heart failure (HF) is a prevalent and debilitating condition that imposes a significant burden on healthcare systems and adversely affects the quality of life of patients worldwide. Comorbidities such as chronic kidney disease (CKD), arterial hypert...

Automated segmentation for early detection of uveal melanoma.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: Uveal melanoma is the most common intraocular malignancy in adults. Current screening and triaging methods for melanocytic choroidal tumours face inherent limitations, particularly in regions with limited access to specialized ocular oncol...

A deep learning approach to explore the association of age-related macular degeneration polygenic risk score with retinal optical coherence tomography: A preliminary study.

Acta ophthalmologica
PURPOSE: Age-related macular degeneration (AMD) is a complex eye disorder affecting millions worldwide. This article uses deep learning techniques to investigate the relationship between AMD, genetics and optical coherence tomography (OCT) scans.