Risk prediction model for progression of type 2 diabetic nephropathy with and without metabolic syndrome: a retrospective cohort study by Yuan Fang, Yuan Fang, Yuan Fang, Siyi Rao, Siyi Rao, Siyi Rao, Yongjie Zhuo, Yongjie Zhuo, Yongjie Zhuo, Jiaqun Lin, Jiaqun Lin, Jiaqun Lin, Xiaohong Zhang, Xiaohong Zhang, Xiaohong Zhang, Jianxin Wan, Jianxin Wan, Jianxin Wan

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Mixed multi-branch feature fusion model for efficient automatic building extraction from high-resolution remote sensing images by Yaohui Liu, Shuzhe Zhang, Xinkai Wang, Taoyi Chen, Hu Jiang, Fei Su

“…Firstly, we designed a Mixed Multi-Branch Feature Fusion (MMFF) module, which performs multi-dimensional weighted fusion on the feature information captured by the Transformer. …”
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Genomic and metabolic network properties in thermophiles and psychrophiles compared to mesophiles by Amal Saeed Alblooshi, Muhammad Ibtisam Nasar, Syed Sabih Ur Rehman, Mohammad Tauqeer Alam

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Studying the performance of YOLOv11 incorporating DHSA BRA and PPA modules in railway track fasteners defect detection by Chengwei Zhang, Jiawei Zhu, Yihao Ma, Qingmei Huang

“…Finally, we add the PPA (Parallelized Patch-Aware Attention) module to the original neck network to enhance multi-scale feature extraction, specifically for small object detection.To validate the model, we created a dataset and conducted experiments. …”
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Accurate multi-category student performance forecasting at early stages of online education using neural networks by Naveed Ur Rehman Junejo, Muhammad Wasim Nawaz, Qingsheng Huang, Xiaoqing Dong, Chang Wang, Gengzhong Zheng

“…Novel features engineering has been utilized to predict students’ performance across multiple categories at early stages of courses. …”
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A Two-Stage Deep Fusion Integration Framework Based on Feature Fusion and Residual Correction for Gold Price Forecasting by Cihai Qiu, Yitian Zhang, Xunrui Qian, Chuhang Wu, Jiacheng Lou, Yang Chen, Yansong Xi, Weijie Zhang, Zhenxi Gong

“…Nonetheless, traditional single prediction models usually suffer from limited predictive performance and fail to capture complex variability of market behavior. …”
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Understanding shading through home-use experience, measurement and modelling by Magdalena Baborska-Narożny, Karol Bandurski, Magdalena Grudzińska

“…Insufficient application of the socio-technical influences on residential energy ‘optimisation’ exacerbates the energy performance gap. This is evident in the modelling of energy and thermal performance. …”
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Optimization of Rockburst Grade Prediction Model Based on Multidimensional Feature Selection: Integrated Learning and Index System Correlation Analysis by Jiayang Chen, Xuebin Xie

“…The results show that tree models (e.g., CatBoost, LightGBM, etc.) are naturally resistant to multicollinearity, and PCA preprocessing destroys their nonlinear feature relationships, leading to performance degradation. …”
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Joint Exploitation of Physical-Layer and Artificial Features for Privacy-Preserving Distributed Source Camera Identification by Hui Tian, Haibao Chen, Yuyan Zhao, Jiawei Zhang

“…In this paper, we propose a novel privacy-preserving distributed source camera identification scheme that jointly exploits both physical-layer fingerprint features and a carefully designed artificial tag. Specifically, we build a hybrid fingerprint model by combining sensor level hardware fingerprints with artificial tag features to characterize the unique identity of the camera in a digital image. …”
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AI driven prediction of early age compressive strength in ultra high performance fiber reinforced concrete by Mohamed Abdellatief, Wafa Hamla, Hassan Hamouda

“…As part of evaluating model performance and conducting error analysis, this study investigated differences in prediction accuracy among five models across training and testing datasets. …”
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Spectral wavelength range influences the performance of chemometric models estimating various foliar functional traits by Minjee Park, Lorenzo Cotrozzi, Geoffrey M. Williams, Matthew D. Ginzel, Michael V. Mickelbart, Douglass F. Jacobs, John J. Couture

“…For complex functional traits, however, there is a lack of well‐defined absorption features and features may be unevenly distributed across the reflectance spectrum, suggesting that the influence of wavelength ranges on the performance of chemometric models is potentially important for accurately estimating foliar functional traits. …”
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Leveraging federated learning for DoS attack detection in IoT networks based on ensemble feature selection and deep learning models by Tasneem Qasem Al-Ghadi, Selvakumar Manickam, I. Dewa Made Widia, Eka Ratri Noor Wulandari, Shankar Karuppayah

“…To enhance model efficiency, we apply filter-based feature selection techniques, including Variance Threshold, Mutual Information, Chi-square, ANOVA, and L1-based methods, and employ an ensemble feature selection approach by combining them through a union operation. …”
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Reverb and Noise as Real-World Effects in Speech Recognition Models: A Study and a Proposal of a Feature Set by Valerio Cesarini, Giovanni Costantini

“…Verification models were trained on clean data using MFCCs, RASTA features, or their combination as inputs. …”
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A multi-model feature fusion based transfer learning with heuristic search for copy-move video forgery detection by Hessa Alfraihi, Muhammad Swaileh A. Alzaidi, Hamed Alqahtani, Abdulbasit A. Darem, Ali M. Al-Sharafi, Ahmad A. Alzahrani, Menwa Alshammeri, Abdulwhab Alkharashi

“…Next, the ECMVFD-FTLTDO technique employs a fusion-based transfer learning (TL) process comprising three models: ResNet50, MobileNetV3, and EfficientNetB7 to capture diverse spatial features across various scales, thereby enhancing the capability of the model to distinguish authentic content from tampered regions. …”
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Building radiomics models based on ACR TI-RADS combining clinical features for discriminating benign and malignant thyroid nodules by Xingxing Chen, Xingxing Chen, Lili Zhang, Bin Chen, Jiajia Lu

“…The diagnostic performance of different models was calculated and compared using the area under the receiver operating curve (AUC) and the corresponding sensitivity and specificity.ResultsEight radiomics features were independent signatures for predicting malignant TNs, with malignant TNs having higher Rad-scores in both cohorts (P < 0.05). …”
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Modelling radiological features fusion and explainable AI in pneumonia detection: A graph- based deep learning and transformer approach by Pratham Kaushik, Eshika Jain, Vinay Kukreja, Shanmugasundaram Hariharan, Murugaperumal Krishnamoorthy, Vandana Ahuja, Abhishek Bhattacherjee, Rajesh Kumar Kaushal, Shih-Yu Chen

“…The classification model incorporated feature fusion, combining handcrafted radiological features with transformer-based feature extraction. …”
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Hyperparameter Optimization of ANN, SVM, and KNN Models for Classification of Hazelnuts Images Based on Shell Cracks and Feature Selection Method by H. Bagherpour, F. Fatehi, A. Shojaeian, R. Bagherpour

“…The results indicated that the SFFS method had a greater effect on improving the performance of the models than the PCA method. However, there was no significant difference between the performance of the models developed with combined features (98.00%) and that of the models using individual features (98.67%). …”
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Slim multi-scale convolutional autoencoder-based reduced-order models for interpretable features of a complex dynamical system by Philipp Teutsch, Philipp Pfeffer, Mohammad Sharifi Ghazijahani, Christian Cierpka, Jörg Schumacher, Patrick Mäder

“…They can learn nonlinear transformations directly from data, without prior knowledge of the system. However, the features generated by such models lack interpretability. …”
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TSAS—YOLOv8: An Optimization Detection Model for Capturing Small Target Features and Processing Key Information by Yongbo Yuan, Linlin Cao

“…This not only reduces the detection accuracy but also undermines the model’s generalization performance. To address this issue, we propose the TSAS-YOLOv8 method. …”
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Integration of metaheuristic based feature selection with ensemble representation learning models for privacy aware cyberattack detection in IoT environments by M. Karthikeyan, R. Brindha, Maria Manuel Vianny, V. Vaitheeshwaran, Mrinal Bachute, Sanket Mishra, Bibhuti Bhusan Dash

“…This manuscript proposes an Adaptive Metaheuristic-Based Feature Selection with Ensemble Learning Model for Privacy-Preserving Cyberattack Detection (AMFS-ELPPCD) technique. …”
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