Consistency of model-derived predictive patterns as a function of sample diversity. by Oualid Benkarim (9707986)

Classification accuracy and information transfer rate (ITR) as a function of the measurement set-up and the number of combined trials. by Dovilė Kurmanavičiūtė (21072549)

Confusion matrices of machine learning models trained on data oversampled by SMOTE and data trained with class weights given to the loss function. by Lucas Teoh (12878206)

Data_Sheet_1_A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks.docx by Maria Grazia Puxeddu (10211162)

“…Finally, as a proof of concept, we show an application of the algorithms to real functional brain networks derived from EEG signals collected at rest with closed and open eyes. …”

Resting state functional MRI brain signatures of fast disease progression in amyotrophic lateral sclerosis: a retrospective study by Francesca Trojsi (707124)

“…We aim to investigate brain functional and structural magnetic resonance imaging (MRI) changes in a cohort of ALS patients, examined at diagnosis and clinically monitored over 18 months, in order to early discriminate fast progressors (FPs) from slow progressors (SPs). …”

List of Abbreviations by Gursimran Singh (575288)

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The results of ICA performed using PyNoetic. by Gursimran Singh (575288)

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Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

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Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

The workflow used to analyze imbalanced and balanced sequences. by Solomon Shiferaw Beyene (9143178)

Performances of Naïve Bayes (NB), Multilayer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), Support Vector Machine (SVM) and K- Nearest Neighbors (KNN). by Solomon Shiferaw Beyene (9143178)

Accuracy, sensitivity, specificity and F-score. by Solomon Shiferaw Beyene (9143178)

The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. by Solomon Shiferaw Beyene (9143178)

Out-of-distribution prediction and performance of predictive models as a function of sample diversity. by Oualid Benkarim (9707986)

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

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Penalty functions used in different methods. by Souvik Seal (12437166)

Estimation accuracy across different structural and functional components of the BVEP model. by Meysam Hashemi (4114738)

“…<p>(<b>A</b>) Excitability values used for simulation () versus the estimated values () for a selected brain region (node number 6). As the node dynamics are varied by changing the excitability parameter (functional component), the model inversion by NUTS algorithm demonstrates an accurate and robust estimation by recovering the ground truth. …”

Image_1_Test-retest reliability of modular-relevant analysis in brain functional network.PDF by Xuyun Wen (414454)

“…Considering the repeatability of network partition depends heavily on network size and module detection algorithm, we constructed three types of brain functional networks for each subject by using a set of coarse-to-fine brain atlases and adopted four methods for single-subject module detection and twelve methods for group-level module detection.…”

Data_Sheet_1_Abnormal Brain Functional Network Dynamics in Acute CO Poisoning.docx by Hongyi Zheng (816158)

“…</p><p>Methods: Combining the sliding window method and k-means algorithm, we identified four recurrent dynamic functional cognitive impairment states from resting-state functional magnetic resonance imaging data from 29 patients in the acute phase of carbon monoxide poisoning and 29 healthy controls. …”

Logistic kernel: Power and Type I error for cluster evaluation metric simulations. by Alexandria M. Jensen (6494957)

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