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Localized estimation of event-related neural source activity from simultaneous MEG-EEG with a recurrent neural network.

Neural networks : the official journal of the International Neural Network Society
Estimating intracranial current sources underlying the electromagnetic signals observed from extracranial sensors is a perennial challenge in non-invasive neuroimaging. Established solutions to this inverse problem treat time samples independently wi...

Optimizing graph neural network architectures for schizophrenia spectrum disorder prediction using evolutionary algorithms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The accurate diagnosis of schizophrenia spectrum disorder plays an important role in improving patient outcomes, enabling timely interventions, and optimizing treatment plans. Functional connectivity analysis, utilizing func...

Research on shared control of robots based on hybrid brain-computer interface.

Journal of neuroscience methods
BACKGROUND: With the arrival of the new generation of artificial intelligence wave, new human-robot interaction technologies continue to emerge. Brain-computer interface (BCI) offers a pathway for state monitoring and interaction control between huma...

Cognitive profiles across the psychosis continuum.

Psychiatry research
Cognitive impairments are core features in individuals across the psychosis continuum and predict functional outcomes. Nevertheless, substantial variability in cognitive functioning within diagnostic groups, along with considerable overlap with healt...

Development of Machine Learning Models for Predicting the 1-Year Risk of Reoperation After Lower Limb Oncological Resection and Endoprosthetic Reconstruction Based on Data From the PARITY Trial.

Journal of surgical oncology
BACKGROUND: Oncological resection and reconstruction involving the lower extremities commonly lead to reoperations that impact patient outcomes and healthcare resources. This study aimed to develop a machine learning (ML) model to predict this reoper...

Explainability of artificial neural network in predicting career fulfilment among medical doctors in developing nations: Applicability and implications.

Social science & medicine (1982)
BACKGROUND: Career fulfilment among medical doctors is crucial for job satisfaction, retention, and healthcare quality, especially in developing nations with challenging healthcare systems. Traditional career guidance methods struggle to address the ...

Prediction of individual weight loss using supervised learning: findings from the CALERIE 2 study.

The American journal of clinical nutrition
BACKGROUND: Predicting individual weight loss (WL) responses to lifestyle interventions is challenging but might help practitioners and clinicians select the most promising approach for each individual.

Machine learning-based classification of Parkinson's disease using acoustic features: Insights from multilingual speech tasks.

Computers in biology and medicine
This study advances the automation of Parkinson's disease (PD) diagnosis by analyzing speech characteristics, leveraging a comprehensive approach that integrates a voting-based machine learning model. Given the growing prevalence of PD, especially am...

Temporal dynamic alterations of regional homogeneity in major depressive disorder: a study integrating machine learning.

Neuroreport
Previous studies have found alterations in the local regional homogeneity of brain activity in individuals diagnosed with major depressive disorder. However, many studies have failed to consider that even during resting states, brain activity is dyna...

Renal Cell Carcinoma Discrimination through Attenuated Total Reflection Fourier Transform Infrared Spectroscopy of Dried Human Urine and Machine Learning Techniques.

International journal of molecular sciences
Renal cell carcinoma (RCC) is the sixth most common cancer in men and is often asymptomatic, leading to incidental detection in advanced disease stages that are associated with aggressive histology and poorer outcomes. Various cancer biomarkers are f...