بدائل البحث:
binary classification » image classification (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary complex » ternary complex (توسيع البحث), snare complex (توسيع البحث)
complex binary » complex boundary (توسيع البحث), complex binds (توسيع البحث)
binary b » binary _ (توسيع البحث)
b based » _ based (توسيع البحث), 1 based (توسيع البحث), 2 based (توسيع البحث)
binary classification » image classification (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary complex » ternary complex (توسيع البحث), snare complex (توسيع البحث)
complex binary » complex boundary (توسيع البحث), complex binds (توسيع البحث)
binary b » binary _ (توسيع البحث)
b based » _ based (توسيع البحث), 1 based (توسيع البحث), 2 based (توسيع البحث)
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121
Table_1_Angiotensin System Autoantibodies Correlate With Routine Prognostic Indicators for COVID-19 Severity.docx
منشور في 2022"…Subsequent determination of more complex or late arrival biomarkers may provide further data on severity, mechanisms, and therapeutic options.…"
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122
Steps in the extraction of 14 coordinates from the CT slices for the curved MPR.
منشور في 2025"…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …"
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123
Schematic overview of SINATRA Pro: A novel framework for discovering biophysical signatures that differentiate classes of proteins.
منشور في 2022"…<p><b>(A)</b> The SINATRA Pro algorithm requires the following inputs: <i>(i)</i> (<i>x</i>, <i>y</i>, <i>z</i>)-coordinates corresponding to the structural position of each atom in every protein; <i>(ii)</i> <b>y</b>, a binary vector denoting protein class or phenotype (e.g., mutant versus wild-type); <i>(iii)</i> <i>r</i>, the cutoff distance for simplicial construction (i.e., constructing the mesh representation for every protein); <i>(iv)</i> <i>c</i>, the number of cones of directions; <i>(v)</i> <i>d</i>, the number of directions within each cone; <i>(vi)</i> <i>θ</i>, the cap radius used to generate directions in a cone; and <i>(vii)</i> <i>l</i>, the number of sublevel sets (i.e., filtration steps) used to compute the differential Euler characteristic (DEC) curve along a given direction. …"
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124
Supplementary Material 8
منشور في 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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125
Models and Dataset
منشور في 2025"…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …"
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126
Table 1_Non-obtrusive monitoring of obstructive sleep apnea syndrome based on ballistocardiography: a preliminary study.docx
منشور في 2025"…Furthermore, our approach directly extracts features from BCG signals without employing a complex algorithm to derive respiratory and heart rate signals as often done in literature, further simplifying the algorithm pipeline. …"
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127
DataSheet1_Nucleotide-level prediction of CircRNA-protein binding based on fully convolutional neural network.PDF
منشور في 2023"…<p>Introduction: CircRNA-protein binding plays a critical role in complex biological activity and disease. Various deep learning-based algorithms have been proposed to identify CircRNA-protein binding sites. …"
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128
Table1_Nucleotide-level prediction of CircRNA-protein binding based on fully convolutional neural network.XLSX
منشور في 2023"…<p>Introduction: CircRNA-protein binding plays a critical role in complex biological activity and disease. Various deep learning-based algorithms have been proposed to identify CircRNA-protein binding sites. …"
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129
Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
منشور في 2025"…<br> <br>Conclusion<br><br>The study concludes that the habitat variable, used in isolation, is insufficient to create a safe and reliable mushroom toxicity classification model. The consistent accuracy of 70.28% does not represent a flaw in the SVM. algorithm, but rather the predictive performance ceiling of the feature itself, whose simplicity and class overlap limit the model's discriminatory ability. …"
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130
Distributed Estimation of Principal Support Vector Machines for Sufficient Dimension Reduction
منشور في 2024"…The two distributed algorithms are further adapted to principal weighted support vector machines for sufficient dimension reduction in binary classification. …"
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131
PathOlOgics_RBCs Python Scripts.zip
منشور في 2023"…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …"
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132
DataSheet_1_Deep Learning-Based Mapping of Tumor Infiltrating Lymphocytes in Whole Slide Images of 23 Types of Cancer.pdf
منشور في 2022"…Our new TIL workflow also incorporates automated thresholding to convert model predictions into binary classifications to generate TIL maps. The new TIL models all achieve better performance with improvements of up to 13% in accuracy and 15% in F-score. …"
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133
Structure-based antibody paratope prediction with 3D Zernike descriptors and SVM
منشور في 2019"…Roto-translationally invariant descriptors are computed from circular patches of the antibody surface enriched with a chosen subset of physicochemical properties from the AAindex1 amino acid index set, and are used as samples for a binary classification problem. An SVM classifier is used to distinguish interface surface patches from non-interface ones. …"
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134
Flow diagram of the automatic animal detection and background reconstruction.
منشور في 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). …"
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135
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
منشور في 2025"…</p><p dir="ltr">Encoding: Categorical variables such as surface coating and cell type were grouped into logical classes and label-encoded to enable model compatibility.</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…"