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MSE for ILSTM algorithm in binary classification.
Published 2023“…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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Iterative chart of control factor.
Published 2024“…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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Hyperparameters of the LSTM Model.
Published 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.
Published 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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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
Published 2025“…The binary GWO algorithm identifies the most relevant features from </p><p dir="ltr">dermatological images, eliminating redundancy and reducing the computational burden. …”
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Flow diagram of the proposed model.
Published 2025“…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. …”
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Parameter settings of the comparison algorithms.
Published 2024“…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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ROC curves for the test set of four models.
Published 2025“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”
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The AD-PSO-Guided WOA LSTM framework.
Published 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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Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf
Published 2024“…A support vector machine (SVM) is attractive because binary classification can be represented as an optimization problem, in particular as a Quadratic Unconstrained Binary Optimization (QUBO) model, which, in turn, maps naturally to an Ising model, thereby making annealing—classical, quantum, and hybrid—an attractive approach to explore. …”
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SHAP bar plot.
Published 2025“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”
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Sample screening flowchart.
Published 2025“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”
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Descriptive statistics for variables.
Published 2025“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”
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SHAP summary plot.
Published 2025“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”