The most effective active substances for subfertility treatment. by Uğur Ejder (22683228)

Hyperparameters of the LSTM Model. by Ahmed M. Elshewey (21463867)

“…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. …”

Prediction results of individual models. by Ahmed M. Elshewey (21463867)

“…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. …”

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…The binary GWO algorithm identifies the most relevant features from </p><p dir="ltr">dermatological images, eliminating redundancy and reducing the computational burden. …”

Flow diagram of the proposed model. by Uğur Ejder (22683228)

“…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. …”

ROC curves for the test set of four models. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

The AD-PSO-Guided WOA LSTM framework. by Ahmed M. Elshewey (21463867)

“…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. …”

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging by D. Andrew Brown (6584837)

Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf by Sai Sakunthala Guddanti (17739363)

“…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. …”

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

SHAP bar plot. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

Sample screening flowchart. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

Descriptive statistics for variables. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

SHAP summary plot. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

Display of the web prediction interface. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures by Hongpeng He (348094)

“…Both in silico design and data analysis descriptors and norm index were employed to encode the structural characteristics of binary IL mixtures. The subset of optimal descriptors was screened by combining the genetic algorithm with the multiple linear regression method. …”

Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles by Peter S. Rice (11805875)

“…For this purpose, we have developed a general procedure that we use to model an experimentally relevant 270-atom Fe₁₈₂C₈₈ NP using the neural network-assisted stochastic surface walk global optimization algorithm (SSW-NN). …”

Generalized Tensor Decomposition With Features on Multiple Modes by Jiaxin Hu (1327875)

“…An efficient alternating optimization algorithm with provable spectral initialization is further developed. …”

Table_1_Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique.DOCX by Hasan Zulfiqar (12117255)

“…The obtained features were optimized by using correlation and the mRMR-based algorithm. …”

Bayesian sequential design for sensitivity experiments with hybrid responses by Yuxia Liu (1779592)

“…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. …”