بدائل البحث:
doses optimization » dose optimization (توسيع البحث), dosage optimization (توسيع البحث), based optimization (توسيع البحث)
when optimization » whale optimization (توسيع البحث), other optimization (توسيع البحث), wolf optimization (توسيع البحث)
binary dataset » final dataset (توسيع البحث), binary data (توسيع البحث), ovary dataset (توسيع البحث)
dataset when » dataset n (توسيع البحث), dataset over (توسيع البحث)
binary risk » primary risk (توسيع البحث), dietary risk (توسيع البحث)
doses optimization » dose optimization (توسيع البحث), dosage optimization (توسيع البحث), based optimization (توسيع البحث)
when optimization » whale optimization (توسيع البحث), other optimization (توسيع البحث), wolf optimization (توسيع البحث)
binary dataset » final dataset (توسيع البحث), binary data (توسيع البحث), ovary dataset (توسيع البحث)
dataset when » dataset n (توسيع البحث), dataset over (توسيع البحث)
binary risk » primary risk (توسيع البحث), dietary risk (توسيع البحث)
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
منشور في 2025"…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …"
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ROC curve for binary classification.
منشور في 2024"…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …"
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Confusion matrix for binary classification.
منشور في 2024"…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …"
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Hyperparameters of the LSTM Model.
منشور في 2025"…This effectively balances exploration and exploitation, and addresses the early convergence problem of the original algorithms. To choose the most crucial characteristics of the dataset, the feature selection method employs the binary format of AD-PSO-Guided WOA. …"
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Prediction results of individual models.
منشور في 2025"…This effectively balances exploration and exploitation, and addresses the early convergence problem of the original algorithms. To choose the most crucial characteristics of the dataset, the feature selection method employs the binary format of AD-PSO-Guided WOA. …"
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The AD-PSO-Guided WOA LSTM framework.
منشور في 2025"…This effectively balances exploration and exploitation, and addresses the early convergence problem of the original algorithms. To choose the most crucial characteristics of the dataset, the feature selection method employs the binary format of AD-PSO-Guided WOA. …"
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Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods
منشور في 2022"…Building on existing work, we (i) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (ii) incorporate adaptive shrinkage penalties, (iii) compare these methods through simulation, and (iv) develop an R package <i>miselect</i>. …"
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Testing results for classifying AD, MCI and NC.
منشور في 2024"…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …"
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Summary of existing CNN models.
منشور في 2024"…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …"
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