بدائل البحث:
protein classification » protein quantification (توسيع البحث), emotion classification (توسيع البحث), improved classification (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
based protein » capsid protein (توسيع البحث), based proteomics (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
binary 2 » binary _ (توسيع البحث), binary b (توسيع البحث)
2 based » _ based (توسيع البحث), 1 based (توسيع البحث), ai based (توسيع البحث)
protein classification » protein quantification (توسيع البحث), emotion classification (توسيع البحث), improved classification (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
based protein » capsid protein (توسيع البحث), based proteomics (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
binary 2 » binary _ (توسيع البحث), binary b (توسيع البحث)
2 based » _ based (توسيع البحث), 1 based (توسيع البحث), ai based (توسيع البحث)
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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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105
Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
منشور في 2020"…Here, we propose a solution to address the limitation of identifiable motor activities by using combined MIs (i.e., MIs involving 2 or more body parts at the same time). And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …"
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106
GSE96058 information.
منشور في 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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The performance of classifiers.
منشور في 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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108
Image_1_A predictive model based on random forest for shoulder-hand syndrome.JPEG
منشور في 2023"…</p>Results<p>A binary classification model was trained based on 25 handpicked features. …"
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109
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Bayesian sequential design for sensitivity experiments with hybrid responses
منشور في 2023"…To deal with the problem of complex computation involved in searching for optimal designs, fast algorithms are presented using two strategies to approximate the optimal criterion, denoted as SI-optimal design and Bayesian D-optimal design, respectively. …"
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111
Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease
منشور في 2025"…<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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112
DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx
منشور في 2021"…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …"
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113
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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Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction
منشور في 2020"…Herein, we report a readily generalizable active-learning (AL) accelerated algorithm for identification of electrochemically stable iridium oxide polymorphs of IrO<sub>2</sub> and IrO<sub>3</sub>. …"
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116
Sample image for illustration.
منشور في 2024"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
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117
Comparison analysis of computation time.
منشور في 2024"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
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118
Process flow diagram of CBFD.
منشور في 2024"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
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119
Precision recall curve.
منشور في 2024"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
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120