Application of Radiomics Model of CT Images in the Identification of Ureteral Calculus and Phlebolith by Qiuyue Yu, Jiaqi Liu, Huashan Lin, Pinggui Lei, Bing Fan

“…Then, the maximum correlation minimum redundancy criterion and the least absolute shrinkage and selection operator algorithm were used for texture feature selection. The feature subset with the most predictability was selected to establish the 3D radiomics model. …”
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Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion by Ying Chen, Yuanning Liu, Xiaodong Zhu, Fei He, Hongye Wang, Ning Deng

“…In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. …”
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Orthogonal Capsule Network with Meta-Reinforcement Learning for Small Sample Hyperspectral Image Classification by Prince Yaw Owusu Amoako, Guo Cao, Boshan Shi, Di Yang, Benedict Boakye Acka

“…The OCN-MRL framework employs Meta-RL for feature selection and CapsNet for classification with a small data sample. …”
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Efficient and accurate determination of the degree of substitution of cellulose acetate using ATR-FTIR spectroscopy and machine learning by Frank Rhein, Timo Sehn, Michael A. R. Meier

“…By applying a n-best feature selection algorithm based on the F-statistic of the Pearson correlation coefficient, several relevant areas were identified and the optimized model achieved an improved MAE of 0.052. …”
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A Lightweight Network with Domain Adaptation for Motor Imagery Recognition by Xinmin Ding, Zenghui Zhang, Kun Wang, Xiaolin Xiao, Minpeng Xu

“…Additionally, lightweight experiments were conducted from two perspectives: model structure optimization and data feature selection. The results demonstrated the potential advantages of this method for practical applications in motor imagery recognition systems.…”
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Improving wheat yield prediction through variable selection using Support Vector Regression, Random Forest, and Extreme Gradient Boosting by Juan Carlos Moreno Sánchez, Héctor Gabriel Acosta Mesa, Adrián Trueba Espinosa, Sergio Ruiz Castilla, Farid García Lamont

“…Using clustering, feature selection, and variable combination techniques, particularly agronomic variables such as harvest index (HI) and biomass (BM), provided complementary information to the Normalized Difference Vegetation Index (NDVI). …”
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Enhancing Stock Portfolio Selection with Trapezoidal Bipolar Fuzzy VIKOR Technique with Boruta-GA Hybrid Optimization Model: A Multicriteria Decision-Making Approach by Sunil Kumar Sharma

“…The Boruta-GA approach combines the advantages of the Genetic Algorithm (GA) and Boruta Optimization Algorithm (BOA) methods, implementing the comprehensive feature selection capability of Boruta to detect all relevant features and harnessing the strength of GA to bring about improvement within a wide range of datasets. …”
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Hybrid deep learning approach for brain tumor classification using EfficientNetB0 and novel quantum genetic algorithm by Kerem Gencer, Gülcan Gencer

“…It is aimed to develop the feature selection method. With this hybrid method, high reliability and accuracy in brain tumor classification was achieved. …”
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A Comprehensive Review of Wind Power Prediction Based on Machine Learning: Models, Applications, and Challenges by Zongxu Liu, Hui Guo, Yingshuai Zhang, Zongliang Zuo

“…The review also explores critical aspects such as data preprocessing, feature selection strategies, and model optimization techniques, which significantly enhance prediction accuracy and robustness. …”
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Optimized Novel Text Embedding Approach for Fake News Detection on Twitter X: Integrating Social Context, Temporal Dynamics, and Enhanced Interpretability by Mahmoud AlJamal, Rabee Alquran, Ayoub Alsarhan, Mohammad Aljaidi, Wafa’ Q. Al-Jamal, Ali Fayez Alkoradees

“…Leveraging the CIC Truth Seeker Dataset 2023, we applied SHAP for feature selection and interpretability, ensuring transparency in the model’s predictions. …”
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Automatic Segmentation of Ischemic Stroke Lesions in CT Perfusion Maps Using Deep Learning Networks by Lida Zare Lahijan, Saeed Meshgini, Reza Afrouzian

“…The proposed network architecture includes the 7 Graph Convolutional layer, which can automatically perform feature selection/extraction and classify the resulting feature vector. …”
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Detecting respiratory diseases using machine learning-based pattern recognition on spirometry data by Ahmed I. Taloba, R.T. Matoog

“…Due to issues with dimensionality and computational complexity, the relevant features are selected using Forward Feature Selection (FFS). The classification approach synthesizes two methods, support vector machines, and k-nearest neighbors, to reveal intricate patterns and boundaries in the data. …”
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An intelligent spam detection framework using fusion of spammer behavior and linguistic. by Amna Iqbal, Muhammad Younas, Muhammad Kashif Hanif, Muhammad Murad, Rabia Saleem, Muhammad Aater Javed

“…The problem statement of this research paper revolves around addressing challenges concerning feature selection and evolving spammer behavior and linguistic features, with the goal of devising an efficient model for spam detection. …”
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An AI-based approach to predict delivery outcome based on measurable factors of pregnant mothers. by Michael Owusu-Adjei, James Ben Hayfron-Acquah, Twum Frimpong, Abdul-Salaam Gaddafi

“…This is achieved by adopting effective feature selection technique to estimate variable relationships with the target variable. …”
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Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine) by Chuin-Hen Liew, Song-Quan Ong, David Chun-Ern Ng

“…Recursive Feature Elimination (RFE) was employed for feature selection, and we trained seven supervised classifiers. …”
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Public Housing Allocation Model in the Guangdong-Hong Kong-Macao Greater Bay Area under Clustering Algorithm by Lei Zhang, Xueqing Hu

“…The simulation experiments are performed on the clustering algorithm optimized based on rough set feature selection. On the Chess data set, the optimized clustering algorithm shows an obvious improvement in clustering accuracy and recall rate compared with the traditional clustering algorithms, which are 0.76 and 0.95, respectively. …”
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Preprocessing Data dan Klasifikasi untuk Prediksi Kinerja Akademik Siswa by Takhamo Gori, Andi Sunyoto, Hanif Al Fatta

“…Penelitian ini bertujuan untuk memprediksi kinerja akademik siswa dengan mengintegrasikan metode Correlation-Based Feature Selection (CFS) dan Algoritma Naïve Nayes pada gabungan dataset pelajaran Matematika dan Bahasa Portugis dua sekolah menengah di Portugal. …”
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Prediction of COVID-19 Confirmed, Death, and Cured Cases in India Using Random Forest Model by Vishan Kumar Gupta, Avdhesh Gupta, Dinesh Kumar, Anjali Sardana

“…On this dataset, first, we performed data cleansing and feature selection, then performed forecasting of all classes using random forest, linear model, support vector machine, decision tree, and neural network, where random forest model outperformed the others, therefore, the random forest is used for prediction and analysis of all the results. …”
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Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis by J. Jerome Vasanth, S. Naveen Venkatesh, V. Sugumaran, Vetri Selvi Mahamuni

“…During the machine learning phase, feature selection from the extracted features was carried out using the J48 decision tree algorithm. …”
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Breast Cancer Prediction: A Fusion of Genetic Algorithm, Chemical Reaction Optimization, and Machine Learning Techniques by Md. Rafiqul Islam, Md. Shahidul Islam, Saikat Majumder

“…GA and CRO are used to optimize the feature selection process. It enables machine learning algorithms to predict more accurately. …”
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