Isolation and Characterization of the Adamantinomatous Craniopharyngioma Primary Cells with Cancer-Associated Fibroblast Features by Dongting Chen, Ting Lei, Yulin Wang, Zaitao Yu, Siqi Liu, Ling Ye, Wanfang Li, Qin Yang, Hongtao Jin, Fangjun Liu, Yan Li

“…In this study, we aimed to construct ACP primary cell models for further investigation of tumorigenic and recurrent mechanisms. …”
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Students' performance prediction employing Decision Tree by Abtahi Ahmed, Farzana Akter Nipa, Wasi Uddin Bhuyian, Khaled Md Mushfique, Kamrul Islam Shahin, Huu-Hoa Nguyen, Dewan Md. Farid

“…This study uses the vast power and analytical domain of EDM, combining it with machine learning models, upholding an accurate prediction of students' academic performance. …”
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A Lightweight Forward–Backward Independent Temporal-Aware Causal Network for Speech Emotion Recognition by Sijia Fei, Qiang Feng, Fei Gao

“…Specifically, a forward temporal-aware component constructed with dilated causal convolutions and skip connections is deployed to perform forward sequences feature modeling, which captures forward semantic information and causal relationships in the speech signal. …”
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Students' performance prediction employing Decision Tree by Abtahi Ahmed, Farzana Akter Nipa, Wasi Uddin Bhuyian, Khaled Md Mushfique, Kamrul Islam Shahin, Huu-Hoa Nguyen, Dewan Md. Farid

“…This study uses the vast power and analytical domain of EDM, combining it with machine learning models, upholding an accurate prediction of students' academic performance. …”
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The effect of gravity on hand spatio-temporal kinematic features during functional movements. by Anna Bucchieri, Federico Tessari, Stefano Buccelli, Elena De Momi, Matteo Laffranchi, Lorenzo De Michieli

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Lightweight ECG signal classification via linear law-based feature extraction by Péter Pósfay, Marcell T Kurbucz, Péter Kovács, Antal Jakovác

“…On TwoLeadECG, a minimal configuration—using only the linear law-based transformation (LLT) and a linear decision rule—reaches 73.1% accuracy using just two features. On VPNet, LLT-ECG combined with classifiers like k-nearest neighbors and support vector machines achieves up to 96.4% accuracy, comparable to deep learning models. …”
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Navigation Aids Performance Evaluation for Precision Approaches by Pier Domenico Tromboni, Giovanni B. Palmerini

“…A numerical code referring to the presented analytical model has been implemented and some applications concerning the system's performance evaluation and planning are proposed to illustrate the algorithm capabilities. …”
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Mechanism–Data Collaboration for Characterizing Sea Clutter Properties and Training Sample Selection by Wenhao Chen, Yong Zou, Zhengzhou Li, Shengrong Zhong, Haolin Gan, Aoran Li

“…Moreover, the distribution of training samples captured from dynamic observation conditions is imbalanced. These multi-features extracted from inaccurate models and imbalanced data lead to overfitting or underfitting and degrade detection performance. …”
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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

“…A two-step feature selection strategy combining F-score pre-filtering and XGBoost feature ranking was designed to select the most discriminating feature subset, which was then fed into an XGBoost model for sleep stage classification. …”
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DFC-Net: Dual-Branch Collaborative Feature Enhancement for Cloud Detection in Remote Sensing Images by Wanting Zhou, Yan Mo, Qiaofeng Ou, Shaowei Bai

“…To this end, this article proposes a dual-branch co-optimization network (DFC-Net), which achieves cross-scale feature fusion and detail enhancement through the dual-branch interaction mechanism of global context modeling and local detail sensing. …”
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MHS-Net: A multi-scale heterogeneous synergistic network for single image deraining by Lingfeng Yuan, Minghong Xie

“…However, existing methods often fail to effectively balance global–local feature interactions and adaptive feature fusion in complex rain-streak scenarios. …”
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An interactive address matching method based on a graph attention mechanism by Ming Li, Jialin Su, Zhiyu Song, Juping Qiu, Yongping Lin

“…Method:: Leveraging the hierarchical structure of Chinese addresses, this study introduces the interactive address matching graph attention model (IAMGAM). In the IAMGAM, an attention-based feature interaction method (AFIM) is employed. …”
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Soil liquefaction assessment using machine learning by Gamze Maden Muftuoglu, Kaveh Dehghanian

“…Feature importance methods consist of permutation and Shapley Additive exPlanations (SHAP) importances along with the used model's built-in feature importance method if it exists. …”
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Prediction of Anthocyanin Content in Purple-Leaf Lettuce Based on Spectral Features and Optimized Extreme Learning Machine Algorithm by Chunhui Liu, Haiye Yu, Yucheng Liu, Lei Zhang, Dawei Li, Junhe Zhang, Xiaokai Li, Yuanyuan Sui

“…Finally, dung beetle optimization (DBO), subtraction-average-based optimization (SABO), and the whale optimization algorithm (WOA) optimized the extreme learning machine (ELM) for modeling. The results indicated the following: (1) For the feature band selection methods, the UVE-CARS-SNV-DBO-ELM model achieved an R_m² of 0.8623, an RMSE_m of 0.0098, an R_v² of 0.8617, and an RMSE_v of 0.0095, resulting in an RPD of 2.7192, further demonstrating that UVE-CARS enhances feature band extraction based on UVE and indicating a strong model performance. (2) For the vegetation index, VI3 showed a better predictive accuracy than VI2. …”
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A comprehensive evaluation of deep learning approaches for ground-level ozone prediction across different regions by Guanjun Lin, Hang Zhao, Yufeng Chi

“…Particularly for the Bi-LSTM architecture, as the number of hidden layers increases from 1 to 7, we observe a 12% reduction in R2 performance. Our analysis also identifies the most influential meteorological factors among the top-performing DL models, offering insights for feature selection and optimization in model development. …”
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Fine monitoring method for mangrove wetland ecosystem based on sentinel data fusion and RF optimization by Shuwen Wang, Taisi Chen, Zimin Li, Haitao Sang

“…By weighting the segmented features and organizing them into a 3D framework, the model demonstrated exceptional performance, with a misclassification rate below 0.001 and overall classification accuracy exceeding 98% on benchmark datasets. …”
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REVIEW OF FEATURE SELECTION METHODS USING OPTIMIZATION ALGORITHM (Review paper for optimization algorithm) by Zana O. Hamad

“…The overall results confirmed that the feature selection approach is important in reducing the complexity of any model-based machine learning algorithm and may sometimes result in improved performance of the simulated model.…”
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Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction by Ali M. Hasan, Asaad F. Qasim, Hamid A. Jalab, Rabha W. Ibrahim

“…Subsequently, all extracted features significantly improves the performance of the LSTM network to precisely discriminate between pathological and healthy cases. …”
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Peculiarities of the classification of economically valuable indicators of highbush blueberry varieties of Vaccinium corymbosum L. by С. І. Мельник, Н. С. Орленко, Н. В. Лещук, В. М. Матус, В. А. Павлюк, Н. В. Павлюк

“…To substantiate the features of the classification of morphobiological and economically valuable indicators of highbush blueberry varieties of Vaccinium corymbosum L. …”
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A two-stage recommendation optimization algorithm based on item popularity and user features by Jun Wang, Rongjie Hu

“…The modified Pearson's similarity function is combined with popularity normalization and user features to improve modeling performance. The two-stage recommendation optimization procedure was combined with a collaborative filtering algorithm to improve recommendation precision. …”
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