Fractal dimension of cortical functional connectivity networks & severity of disorders of consciousness by Thomas F. Varley (8446899)

“…<div><p>Recent evidence suggests that the quantity and quality of conscious experience may be a function of the complexity of activity in the brain and that consciousness emerges in a critical zone between low and high-entropy states. …”

Spreadsheets containing the graph parameters, brain areas and network values. by Jafar Zamani (12902504)

Data of PV, WT, FC, and utilized coefficients. by Obaid Aldosari (19797428)

Phase diagram for global archetype model as a function of temperature. by Giulio Ruffini (383994)

Subjects:

Studies with ML classification algorithms for distinguishing ASD and ADHD groups described in subsection 1.2. by Caroline L. Alves (14271413)

Reverse engineering information flow using stimulus-encoding and stimulus-transfer estimation algorithms. by Gabriel Matías Lorenz (21094672)

Binary Networks (Threshold = 0.4) by Majid Saberi (11796824)

Subjects:

Model parameter estimates and standard errors for pooled-ERGM analysis of brain functional connectivity networks. by Fan Yin (170408)

MAP estimates and posterior standard deviations, conjugate Bayesian analysis of brain functional connectivity networks. by Fan Yin (170408)

BNA Neuromarker scores as a function of LEDD. by Sharon Hassin-Baer (420354)

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Classification accuracy as a function of random walk length. by Inon Zuckerman (8399517)

Fold Change (FC) in protein levels among non-survivors compared to survivors in 40 CERES participants. by Yue Ren (1311615)

Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. by Borjan Milinkovic (21349908)

Comparison of performance obtained by our approach with other state-of-the-art algorithms. by Sajad Mousavi (6672425)

Average classification accuracies for fft and stack methods, LSTM, Bi-LSTM, and CNN algorithms. by Jamila Akhter (21144252)

Data_Sheet_1_Prediction of motor function in patients with traumatic brain injury using genetic algorithms modified back propagation neural network: a data-based study.docx by Hui Dang (4396087)

“…</p>Conclusion<p>The genetic algorithms modified back propagation neural network can predict motor function in patients with traumatic brain injury, which can be used as a reference for risk and prognosis assessment and guide clinical decision-making.…”

Data_Sheet_1_Prediction of motor function in patients with traumatic brain injury using genetic algorithms modified back propagation neural network: A data-based study.docx by Hui Dang (4396087)

“…</p>Conclusion<p>The genetic algorithms modified back propagation neural network can predict motor function in patients with traumatic brain injury, which can be used as a reference for risk and prognosis assessment and guide clinical decision-making.…”

Generating the PSC kernel using a double exponential function. by Alireza Ghadimi (13839874)

Classification accuracy as a function of the amount of training data. by Dovilė Kurmanavičiūtė (21072549)

Local magnetization and susceptibility as a function of temperature from Metropolis simulations with the global archetype model. by Giulio Ruffini (383994)

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