Embedded feature fusion for multi-label criteria selection via local search strategy and particle swarm optimization by Suhua Chen, Xu Fang, Feng Zhai, Li Wang, Lin Lv

“…Despite its importance, feature selection remains a complex issue without straightforward solutions, and various approaches using AI and evolutionary algorithms have been proposed to tackle it. …”
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SCM-DL: Split-Combine-Merge Deep Learning Model Integrated With Feature Selection in Sports for Talent Identification by Didem Abidin, Muhammed G. Erdem

“…The SCM-DL integrated with the RFE_DTC feature selection method achieved the highest performance for six features, yielding an accuracy rate of 97.40% and a Matthews Correlation Coefficient performance rate of 96.6%. …”
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Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

“…In this vein, optimal conductor size selection and phase balancing are among the most common strategies for improving these indicators, which involves dealing with complex optimization problems. …”
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Principles of physical factor selection in the early postoperative period of breast cancer treatment: a randomized controlled study by Inna S. Evstigneeva

“…To develop algorithms for selecting physical factors depending on the clinical and functional state of patients after radical surgical treatment of breast cancer (BC) in the early postoperative period. …”
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A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping by Radhwan A. Saleh, Ahmed M. Al-Areeq, Amran A. Al Aghbari, Mustafa Ghaleb, Mohammed Benaafi, Nabil M. Al‑Areeq, Baqer M. Al-Ramadan

“…Then, the Memo Search Algorithm (MSA), a metaheuristic approach is proposed to efficiently reduce feature space. Through comprehensive comparisons with established algorithms such as the Artificial Bee Colony (ABC) and Gray Wolf Optimizer (GWO), MSA refined the selection, identifying 'elevation’ and 'distance to streams’ as optimal factors. …”
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Integrated feature selection-based stacking ensemble model using optimized hyperparameters to predict breast cancer with smart web application by Rajib Kumar Halder, Marzana Akter Lima, Mohammed Nasir Uddin, Md.Aminul Islam, Adri Saha

“…Early detection is paramount as it significantly improves survival rates and reduces the complexity and cost of treatment. Machine learning has revolutionized this field, providing more precise, efficient, and personalized diagnostic methods. …”
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Optimization Design of the Transmission System of Small-size Shrub Brush Cutter based on MATLAB by Yang Chunmei, Guo Minghui, Ma Yan, Liu Qianjun, Yang Tie

“…By determining the objective function of the transmission system,selecting the independent design variables,determining the constraints,the mathematical model of transmission system is established.The analysis and optimization of the design variables,objective function and the boundary conditions are carried out,the complex method optimization program of MATLAB is written,and by using its powerful ability of optimization design to optimize the transmission system of the brush cutter. …”
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An Effective and Interpretable Sleep Stage Classification Approach Using Multi-Domain Electroencephalogram and Electrooculogram Features by Xin Xu, Bei Zhang, Tingting Xu, Junyi Tang

“…Recent research efforts on automated sleep staging have focused on complex deep learning architectures that have achieved modest improvements in classification accuracy but have limited real-world applicability due to the complexity of model training and deployment and a lack of interpretability. …”
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Enhancing credit card fraud detection: highly imbalanced data case by Dalia Breskuvienė, Gintautas Dzemyda

“…It has been specifically designed to efficiently process and analyze vast and complex datasets commonly encountered in the financial sector, showcasing adaptability to the dynamic nature of big data environments. …”
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Synthetic graphs for link prediction benchmarking by Alexey Vlaskin, Eduardo G Altmann

“…Predicting missing links in complex networks requires algorithms that are able to explore statistical regularities in the existing data. …”
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Intelligent design of Fe–Cr–Ni–Al/Ti multi-principal element alloys based on machine learning by Kang Xu, Zhengming Sun, Jian Tu, Wenwang Wu, Huihui Yang

“…Multi-principal element alloys (MPEAs), distinguished by their complex compositions and exceptional mechanical properties, pose significant challenges for conventional predictive approaches in mechanical property optimization. …”
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Petrographic image classification of complex carbonate rocks from the Brazilian pre-salt using convolutional neural networks by Mateus Basso, João Paulo da Ponte Souza, Guilherme Furlan Chinelatto, Luis Augusto Antoniossi Mansini, Alexandre Campane Vidal

“…The use of ML enables the analysis of large datasets, the identification of complex patterns, and can save time and reduce costs compared to conventional approaches. …”
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Genotypic and Phenotypic Association of Agronomic Features in Triticale Genotypes under Drought Stress Conditions by Hassan Basiri, Omid Alizadeh, Forud Bazrafshan, Mehdi Zare, Mohammad Yazdani

“…However, creating diversity, selecting genotypes, and studying different traits will help scientists in this direction. …”
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TCR-engaging scaffolds selectively expand antigen-specific T-cells with a favorable phenotype for adoptive cell therapy by Marco Donia, Özcan Met, Julie Westerlin Kjeldsen, Sine Reker Hadrup, Inge Marie Svane, Arianna Draghi, Anders Handrup Kverneland, Christina Heeke, Siri Amanda Tvingsholm, Marcus Svensson Frej, Vibeke Mindahl Rafa, Ulla Kring Hansen, Maria Ormhøj, Alexander Tyron, Agnete W P Jensen, Mohammad Kadivar, Amalie Kai Bentzen, Kamilla K Munk, Gitte N Aasbjerg, Jeppe S H Ternander, Tripti Tamhane, Christian Schmess, Samuel A. Funt, Søren Nyboe Jakobsen

“…The resulting T-cell products were assessed for phenotypic and functional characteristics.Results We identified an optimal Ag-scaffold for expansion of T-cells for ACT, carrying pMHC and interleukin-2 (IL-2) and IL-21, with which we efficiently expanded both virus-specific and tumor-specific CD8+ T cells from peripheral blood of healthy donors and patients, respectively. …”
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A data-centric and interpretable EEG framework for depression severity grading using SHAP-based insights by Anruo Shen, Jingnan Sun, Xiaogang Chen, Xiaorong Gao

“…However, most EEG-based machine learning diagnostic studies focus on boosting classification accuracy through complex algorithms and small, homogenous datasets. …”
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Optimization Method of Wind Turbine Locations in Complex Terrain Areas Using a Combination of Simulation and Analytical Models by Dinh Van Thin, Le Quang Sang, Nguyen Huu Duc

“…For areas with complex terrain, wind resource characteristics depend largely on terrain features, so the selection of turbine installation locations is very important. …”
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PROBLEMS OF FORMATION OF FINANCIAL-INVESTMENT PROJECTION OF A BALANCED SCORECARD IN VALUE-BASED ENTERPRISES OF MINING-METALLURGICAL COMPLEX by S. Faizova, M. Ivanova, S. Sannikova, O. Varyanichenko

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Recruitment of a SAP18-HDAC1 complex into HIV-1 virions and its requirement for viral replication. by Masha Sorin, Jennifer Cano, Supratik Das, Sheeba Mathew, Xuhong Wu, Kelvin P Davies, Xuanling Shi, S-W Grace Cheng, David Ott, Ganjam V Kalpana

“…INI1/hSNF5 is a component of the SWI/SNF complex that interacts with HIV-1 IN, is selectively incorporated into HIV-1 (but not other retroviral) virions, and modulates multiple steps, including particle production and infectivity. …”
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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

“…The concept of explainable artificial intelligence was adopted by incorporating permutation feature importance ranking and Shapley Additive explanations values to identify the feature set that optimized a model's performance while reducing computational complexity. The proposed explainable artificial intelligence feature selection method was compared to conventional feature selection techniques, including mutual information, chi-square coefficient, maximal information coefficient, Fisher separation criterion and variance thresholding. …”
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Enhancing IDS for the IoMT based on advanced features selection and deep learning methods to increase the model trustworthiness. by Ahmed Muqdad Alnasrallah, Maheyzah Md Siraj, Hanan Ali Alrikabi

“…This study indicates that the proposed strategy decreases computational complexity and enhances IDS efficiency in resource-constrained IoMT environments.…”
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