General model for best feature extraction of EEG using discrete wavelet transform wavelet family and differential evolution by Ahmad al-Qerem, Faten Kharbat, Shadi Nashwan, Staish Ashraf, khairi blaou

“…This article presents an efficient model for EEG classification by considering feature extraction and selection. …”
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Multiscale Sample Entropy-Based Feature Extraction with Gaussian Mixture Model for Detection and Classification of Blue Whale Vocalization by Oluwaseyi Paul Babalola, Olayinka Olaolu Ogundile, Vipin Balyan

“…To improve the accuracy of classification models, a GMM-based feature selection method is proposed, which evaluates both positively and negatively correlated features while considering inter-feature correlations. …”
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Research on High Arch Dam Deformation Monitoring Model with Deep Capturing Related Features in Factor-time Dimensions by XUE Jianghan, ZHANG Pengtao, TIAN Jichen, LU Xiang, CHEN Jiankang, Guo Yinju

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Formalization of Hybrid Systems Models for Port Terminal Management With Considering of Key Performance Indicators by Liudmyla L. Nikolaieva, Taras Y. Omelchenko, Oleksandr V. Haichenia

“…ABSTRACT New way of formalizing hybrid systems in models for managing the process of vessel unloading is caused by the significant increase in container transportation around the world over the past decade. …”
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Systematic Approach for Malware Detection in IoT Devices: Enhancing Security and Performance by Vasudeva Pai, B. H. Karthik Pai, G. S. Sudhiksha, Vandya Kamath, K. Varsha, S. Manjunatha

“…These include ensemble methods such as Bagging, Stacking, Voting, AdaBoost, and H2O AutoML, as well as advanced models such as sparse neural networks with pruning and feature selection and regularized classifiers L1. …”
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Pregnancy probability prediction models based on 5 machine learning algorithms and comparison of their performance by REN Chao, REN Chao, YANG Huan, ZHOU Niya, ZHOU Niya

“…Objective‍　‍To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes. …”
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Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome by Pedro Pons-Suñer, François Signol, Noemi Alvarez, Claudia Sargas, Sara Dorado, Jose Vicente Gil Ortí, Juan A. Delgado Sanchis, Marta Llop, Laura Arnal, Rafael Llobet, Juan-Carlos Perez-Cortes, Rosa Ayala, Eva Barragán

“…Methods A dataset of 568 patients, including demographic, clinical, genetic (VAF), and cytogenetic information, was created by combining data from Hospital 12 de Octubre (Madrid, Spain) and Instituto de Investigación Sanitaria La Fe (Valencia, Spain). Feature selection based on an enhanced version of SEQENS was conducted for each time point, followed by the comparison of four classifiers (XGBoost, Multi-Layer Perceptron, Logistic Regression and Decision Tree) to assess the impact of feature selection on model performance. …”
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Preoperative prediction of recurrence risk factors in operable cervical cancer based on clinical-radiomics features by Xue Du, Xue Du, Chunbao Chen, Lu Yang, Yu Cui, Min Li

“…Three clinical features were screened to construct a clinical model. …”
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Research of Large Inflow Angles BEMT-Based Analytical–Numerical Performance Evaluation Model by Carlos Sosa Henríquez, Martynas Lendraitis

“…The algorithm’s design, range, and analytical features are clarified, indicating its potential to improve performance analysis, particularly for blades with substantial pitch variations. …”
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Modeling and Performance Evaluation of Hybrid Classical–Quantum Serverless Computing Platforms by Claudio Cicconetti

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A recognition model for winter peach fruits based on improved ResNet and multi-scale feature fusion by Yan Li, Chunping Li, Tingting Zhu, Shurong Zhang, Li Liu, Zhanpeng Guan

“…The WinterPeachNet model achieves a comprehensive improvement in network performance by integrating depthwise separable inverted bottleneck ResNet (DIBResNet), bidirectional feature pyramid network (BiFPN) structure, GhostConv module, and the YOLOv11 detection head (v11detect). …”
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Hybrid Symbolic Regression and Machine Learning Approaches for Modeling Gas Lift Well Performance by Samuel Nashed, Rouzbeh Moghanloo

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A hybrid machine learning model with attention mechanism and multidimensional multivariate feature coding for essential gene prediction by Wu Yan, Fu Yu, Li Tan, Li Mengshan, Xie Xiaojun, Zhou Weihong, Sheng Sheng, Wang Jun, Wu Fu-an

“…Additionally, the cross-species predictive performance of the model was evaluated through cross-validation. …”
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Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features by Jingna Tao, Zhongmian Zhang, Linghan Meng, Liju Zhang, Jiaqi Wang, Zhihong Li

“…BackgroundThis study aimed to construct and validate diagnostic models for the Operative Link on Gastritis Assessment (OLGA) and Operative Link on Gastric Intestinal Metaplasia Assessment (OLGIM) staging systems using three different methodologies based on magnifying endoscopy with narrow-band imaging (ME-NBI) features, to evaluate model performance, and to analyse risk factors for high-risk OLGA/OLGIM stages.MethodsWe enrolled 356 patients who underwent white-light endoscopy and ME-NBI at the Department of Gastroenterology, Dongzhimen Hospital, Beijing University of Chinese Medicine, between January 2022 and September 2023. …”
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A generalizable model for the facial recognition of sika deer with enhanced cross-domain performance by Ye Mu, Jinghuan Hu, Zhipeng Li, Heyang Wang, He Gong, Yu Sun, Tianli Hu

“…Experimental results demonstrate state-of-the-art performance, achieving 98.7 % recognition accuracy and a threefold reduction in computational load compared to baseline models. …”
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A machine-learned model for predicting weight loss success using weight change features early in treatment by Farzad Shahabi, Samuel L. Battalio, Angela Fidler Pfammatter, Donald Hedeker, Bonnie Spring, Nabil Alshurafa

“…The SMART-trained model showed generalizable performance with no substantial difference across studies.…”
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Comparative Analysis of Machine Learning and Deep Learning Models for Lung Cancer Prediction Based on Symptomatic and Lifestyle Features by Bireswar Dutta

“…The model performance was assessed using K-fold cross-validation and 80/20 train/test splitting. …”
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CLA-BERT: A Hybrid Model for Accurate Encrypted Traffic Classification by Combining Packet and Byte-Level Features by Hong Huang, Yinghang Zhou, Feng Jiang

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A non-intrusive load monitoring algorithm based on real-time feature extraction and deep learning model by Behrooz Taheri, Mostafa Sedighizadeh, Mohammad Reza Nasiri, Alireza Sheikhi Fini

“…This innovation combines a two-stage feature extraction method based on Soft Sifting Stopping Criterion Empirical Mode Decomposition (SSSC-EMD) and an adaptive deep learning model with architecture tuning capabilities, in order to improve the performance and accuracy of home appliance detection under different conditions.…”
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Enhancing depression recognition through a mixed expert model by integrating speaker-related and emotion-related features by Weitong Guo, Qian He, Ziyu Lin, Xiaolong Bu, Ziyang Wang, Dong Li, Hongwu Yang

“…Thus, it outperforms state-of-the-art deep learning methods that use speech features. Additionally, our approach shows strong performance across Chinese and English speech datasets, highlighting its effectiveness in addressing cultural variations.…”
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