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A Compact Graph Convolutional Network With Adaptive Functional Connectivity for Seizure Prediction.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Seizure prediction using EEG has significant implications for the daily monitoring and treatment of epilepsy patients. However, the task is challenging due to the underlying spatiotemporal correlations and patient heterogeneity. Traditional methods o...

High accuracy in lower limb alignment analysis using convolutional neural networks, with improvements needed for joint-level metrics.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Evaluation of long-leg standing radiographs (LSR) is a standardised procedure for analysis of primary or secondary deformities of the lower limbs. Deep-learning convolutional neural networks (CNN) offer the potential to enhance radiological ...

A machine-learning model of academic resilience in the times of the COVID-19 pandemic: Evidence drawn from 79 countries/economies in the PISA 2022 mathematics study.

The British journal of educational psychology
BACKGROUND: Given that students from socio-economically disadvantaged family backgrounds are more likely to suffer from low academic performance, there is an interest in identifying features of academic resilience, which may mitigate the relationship...

Deep learning enables accurate brain tissue microstructure analysis based on clinically feasible diffusion magnetic resonance imaging.

NeuroImage
Diffusion magnetic resonance imaging (dMRI) allows non-invasive assessment of brain tissue microstructure. Current model-based tissue microstructure reconstruction techniques require a large number of diffusion gradients, which is not clinically feas...

Optimizing Real-Time MI-BCI Performance in Post-Stroke Patients: Impact of Time Window Duration on Classification Accuracy and Responsiveness.

Sensors (Basel, Switzerland)
Brain-computer interfaces (BCIs) are promising tools for motor neurorehabilitation. Achieving a balance between classification accuracy and system responsiveness is crucial for real-time applications. This study aimed to assess how the duration of ti...

Deep learning-based reconstruction improves the image quality of low-dose CT enterography in patients with inflammatory bowel disease.

Abdominal radiology (New York)
PURPOSE: Lifelong re-examination of CT enterography (CTE) in patients with inflammatory bowel disease (IBD) may be necessary, and reducing radiation exposure during CT examinations is crucial. We investigated the potential application of deep learnin...

Predicting overall survival in anaplastic thyroid cancer using machine learning approaches.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Anaplastic thyroid carcinoma (ATC) is a highly aggressive and lethal thyroid cancer subtype with a poor prognosis. Recent advancements in machine learning (ML) have the potential to improve survival predictions. This study aimed to develop a...

Characterizing daily physical activity patterns with unsupervised learning via functional mixture models.

Journal of behavioral medicine
Physical inactivity is a significant public health concern. Consideration of inter-individual variations in physical activity (PA) trends can provide additional information about the groups under study to aid intervention design. This study aims to i...

Integration of an electronic hand hygiene auditing system with electronic health records using machine learning to predict hospital-acquired infection in a health care setting.

American journal of infection control
BACKGROUND: Hospital-acquired infections (HAIs) increase morbidity, mortality, and health care costs. Effective hand hygiene (HH) is crucial for prevention, but achieving high compliance remains challenge. This study explores using machine learning t...