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Optimizing Uterine Synchronization Analysis in Pregnancy and Labor through Window Selection and Node Optimization
Following that, several neural network and machine learning methods are applied to the best windows and best nodes to categorize pregnancy and labor contractions, based on the different input parameters (connectivity method alone, connectivity method plus graph parameters, best nodes, all nodes, best windows, all windows).
The Forecastability of Underlying Building Electricity Demand from Time Series Data
Forecasting building energy consumption has become a promising solution in Building Energy Management Systems for energy saving and optimization.
An Electroencephalography connectome predictive model of major depressive disorder severity
Using regression models and three independent EEG datasets (N=328), we tested whether resting state functional connectivity could predict individual depression score.
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