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

Performance comparison of RWDisEnh on the heterogeneous network of diseases and enhancers and that on the enhancer functional interaction network and the disease similarity network... by Duc-Hau Le (603529)

Core genes were selected through PPI analysis based on three algorithms. by Dong-Hee Han (140305)

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

Subjects:

Distinct microbial and functional composition between age groups. by Elio L. Herzog (11576876)

Subjects: “…applying independent algorithms…”

The algorithm for the same-day surgery protocol. by Magnus Tveit (11442200)

Summary of results of naïve Bayes algorithms. by Christopher E. Niemczak (8586861)

“…<div><p>Importance</p><p>Predicting neurocognitive deficits using complex auditory assessments could change how cognitive dysfunction is identified, and monitored over time. …”

Characteristic chart of algorithm efficiency. by Wang Xiaoqian (10502222)

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

Subjects:

Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

Descriptive statistics of the dataset with mean, standard deviation (SD), median, and the lower (quantile 5%) and upper (quantile 95%) boundary of the 90% confidence interval. by Achim Langenbucher (3156741)

Subjects:

Optimised formula constants for the SRKT, the Hoffer Q, the Holladay 1, Haigis (with optimised a0 and preset values a1 = 0.4 / a2 = 0.1, Haigis1; and with optimised a0 / a1 / a2 co... by Achim Langenbucher (3156741)

Subjects:

Cumulative density function (CDF) of prediction error (PE, achieved spherical equivalent–formula predicted spherical equivalent) for the SRKT, Hoffer Q, Holladay1, Haigis (with opt... by Achim Langenbucher (3156741)

Subjects:

Prediction error (PE) as the difference between achieved and formula predicted spherical equivalent for 8 different statistical metrics of formula constant optimisation and various... by Achim Langenbucher (3156741)

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Dice score for various <i>α</i> values (from the Eq 8) for the tracking of the CST and for the iFOD and PTT algorithms. by Thomas Durantel (20933812)

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Five types of Beta functions considered. by Luan Carlos de Sena Monteiro Ozelim (16914117)

Improved BP network algorithm flow. by Wang Xiaoqian (10502222)

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

“…<div><p>Chest X-ray image classification plays an important role in medical diagnostics. Machine learning algorithms enhanced the performance of these classification algorithms by introducing advance techniques. …”

Membership function (1^st input). by Tuan Anh Nguyen (121944)