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.…”

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

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

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TanH, ReLU, Leaky ReLU, and ELU activation functions. by Javier León (162217)

Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

Representative neurons and their corresponding step functions. by Reem Khalil (10898163)

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Comparison between the non-sensory motor and sensory–motor algorithms. by Hiroyuki Ichijo (13891153)

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Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”

Performance of various deep learning models from PyNoetic’s classification module on the Motor Imagery decoding task. by Gursimran Singh (575288)

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Correlation between the BNA neuromarker linear scores and the mUPDRS scores. by Sharon Hassin-Baer (420354)

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The BNA neuromarker characteristics. by Sharon Hassin-Baer (420354)

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Features of the BNA neuromarker. by Sharon Hassin-Baer (420354)

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Schematic depiction of BNA scores. by Sharon Hassin-Baer (420354)

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Demographic and clinical characteristics of participants included in the BNA neuromarker. by Sharon Hassin-Baer (420354)

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Results of the cognitive tasks performance. by Sharon Hassin-Baer (420354)

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Comparison between algorithm and expert cell counting. by Adam L. Tyson (10892822)

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Comparison of algorithms in two cases. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”