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121
Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
Published 2025“…The single predictor variable was the mushroom habitat, a categorical feature that was preprocessed using the One-Hot Encoding technique, resulting in seven distinct binary variables. …”
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Steps in the extraction of 14 coordinates from the CT slices for the curved MPR.
Published 2025“…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …”
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124
GSE96058 information.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
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125
The performance of classifiers.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
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128
Bayesian sequential design for sensitivity experiments with hybrid responses
Published 2023“…<p>In experimental design, a common problem seen in practice is when the result includes one binary response and multiple continuous responses. …”
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129
Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease
Published 2025“…Regions of interest were delineated using 3D Slicer software, and radiomics features were extracted with the Pyradiomics package in Python. <i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …”
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130
Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx
Published 2020“…In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. …”
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133
DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx
Published 2024“…Utilizing the binary “One-vs-Rest” strategy, the model based on the RadImageNet dataset demonstrated superior efficacy in predicting Class 0, achieving an AUC of 0.969 and accuracy of 0.863. …”
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134
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136
Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model
Published 2025“…This framework integrates a novel biologically inspired optimization algorithm, the Indian Millipede Optimization Algorithm (IMOA), for effective feature selection. …”
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137
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138
Supplementary Material 8
Published 2025“…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…”
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139
Seed mix selection model
Published 2022“…GA: A Package for Genetic Algorithms in R. <em>Journal of Statistical Software</em>, <em>53</em>, 1-37. http://www.jstatsoft.org/v53/i04</p> <p>Scrucca, L. (2017). …”
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140
Flow diagram of the automatic animal detection and background reconstruction.
Published 2020“…(E) The threshold value is calculated based on the histogram: it is the mean of the image subtracted by 4 (optimal value defined by trial and error). …”