Machine Learning and Deep Learning Hybrid Approach Based on Muscle Imaging Features for Diagnosis of Esophageal Cancer by Yuan Hong, Hanlin Wang, Qi Zhang, Peng Zhang, Kang Cheng, Guodong Cao, Renquan Zhang, Bo Chen

“…This study innovatively combines muscle imaging features with conventional esophageal imaging features to construct deep learning diagnostic models. …”
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Clinical application of combined CT radiomics and clinical features in survival prediction for pancreatic ductal adenocarcinoma patients by LI Ke, LI Ke, CHEN Jiafei, YANG Jing

“…The integrated model combining 2 types of features together demonstrated improved performance with an AUC value of 0.906 (95%CI: 0.842~0.970) and 0.872 (95%CI: 0.753~0.992) in the 2 groups. …”
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YOLO-MAD: Multi-Scale Geometric Structure Feature Extraction and Fusion for Steel Surface Defect Detection by Hantao Ding, Junkai Chen, Hairong Ye, Yanbing Chen

“…The model also shows enhanced recognition performance for most defect categories. …”
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Intelligent Prediction Platform for Sepsis Risk Based on Real-Time Dynamic Temporal Features: Design Study by Mingwei Zhang, Ming Zhong, Yunzhang Cheng, Tianyi Zhang

“…However, the existing sepsis prediction models based on artificial intelligence still have limitations, such as poor real-time performance and insufficient interpretation. …”
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Hybrid Paddy disease classification using optimized statistical feature based transformation technique with explainable AI by M Amudha, Brindha K

“…The next step is to use a Cat Boost classifier to sort the features. Using SHAP analysis and the Cat Boost classifier, this study delves deeper into the model’s classification process and the effects of each feature on the model’s operation. …”
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Optimized Marine Target Detection in Remote Sensing Images with Attention Mechanism and Multi-Scale Feature Fusion by Xiantao Jiang, Tianyi Liu, Tian Song, Qi Cen

“…These components work together to enhance the model’s performance in detecting complex maritime targets by improving its ability to capture multi-scale features, optimize the localization process, and adapt to the large aspect ratios typical of maritime objects. …”
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PolSAR image classification using shallow to deep feature fusion network with complex valued attention by Mohammed Q. Alkhatib, M. Sami Zitouni, Mina Al-Saad, Nour Aburaed, Hussain Al-Ahmad

“…However, the most remarkable performance of the CV-ASDF2Net model is observed with the Flevoland dataset; the model achieves an impressive OA of 96.01% with only a 1% sampling ratio. …”
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An Explainable Deep Learning Network for Environmental Microorganism Classification Using Attention-Enhanced Semi-Local Features by R. Karthik, Armaano Ajay, Akshaj Singh Bisht, Jaehyuk Cho, V. E. Sathishkumar

“…The DenseNet-169 architecture is modified to integrate the EHCR and DASA blocks, allowing the model to focus on semi-local feature extraction for improved feature representation. …”
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Ship crack detection method based on lightweight fast convolution and bidirectional weighted feature fusion network by Chong WANG, Yuhui ZHU

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Investigation of Geometric Characteristics on the Lubricant Performance of Thrust Bearing with Cavitation by L. Kailei, C. Jiayuan, Z. Haoran, Z. Lin, W. Xuze, C. Yu

“…The simulation model considers the impact of geometric characteristics and operational conditions, including the viscoelastic effect, transformation feature, and flow state, to enhance calculation ability. …”
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PERFORMANCE SIMULATION OF A RADAR ANTENNA SYSTEM P-18 by Vadym P. Bunakov, Dmytro S. Zavadskyi, Oleg O. Voloshyn, Sergii Y. Slobodeniuk

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Enhancing credit card fraud detection: the impact of oversampling rates and ensemble methods with diverse feature selection by Mohamed Akouhar, Abdallah Abarda, Mohamed El Fatini, Mohamed Ouhssini

“…The goal of this study is to enhance credit card fraud detection by analyzing oversampling rates to select the optimal one for the highest-performing models and using ensemble techniques based on diverse feature selection approaches. …”
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EEG-based epilepsy detection using CNN-SVM and DNN-SVM with feature dimensionality reduction by PCA by Yousra Berrich, Zouhair Guennoun

“…Abstract This study focuses on epilepsy detection using hybrid CNN-SVM and DNN-SVM models, combined with feature dimensionality reduction through PCA. …”
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基于脑影像及临床特征的机器学习模型预测缺血性卒中后心房颤动 A Machine Learning Model Based on Brain Imaging and Clinical Features for Predicting Atrial Fibrillation Detected after Stroke... by 张栗源1，刘涛2，姜勇1，李子孝1，3，王拥军1，3，杨晓萌1，3(ZHANG Liyuan1, LIU Tao2, JIANG Yong1, LI Zixiao1,3, WANG Yongjun1,3, YANG Xiaomeng1,3 )

“…After retaining independent features, the least absolute shrinkage and selection operator (LASSO) regression algorithm was used for feature selection and to construct a joint prediction model. …”
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A Novel Improvement of Feature Selection for Dynamic Hand Gesture Identification Based on Double Machine Learning by Keyue Yan, Chi-Fai Lam, Simon Fong, João Alexandre Lobo Marques, Richard Charles Millham, Sabah Mohammed

“…This selection allows us to classify and analyze gestures more efficiently, thereby improving models’ performance and interpretability. Compared to commonly used feature selection methods such as Variance Threshold, Select From Model, Principal Component Analysis, Least Absolute Shrinkage and Selection Operator, Artificial Neural Network, and TabNet, Double Machine Learning methods focus more on causal relationships between variables rather than correlations. …”
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Face Recognition Method for Underground Engineering Based on Dual-Target Domain Adaptation and Discriminative Feature Learning by Yongqiang Yu, Cong Guo, Lidan Fan, Jiyun Zhang, Liwei Yu, Peitao Li

“…Although various methods to improve algorithm robustness can enhance the overall model performance, the face recognition accuracy remains insufficient for the large number of blurred and NIR images generated during underground engineering. …”
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Non-parametric feature selection and machine learning based seasonal GHI prediction for SAPV systems in India by Aadyasha Patel, Gnana Swathika O․V․

“…Machine Learning (ML) models can generate precise and reliable GHI forecasts by choosing features that capture such seasonal variations, therefore boosting the performance of SAPV systems. …”
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Sparse Feature-Weighted Double Laplacian Rank Constraint Non-Negative Matrix Factorization for Image Clustering by Hu Ma, Ziping Ma, Huirong Li, Jingyu Wang

“…We also propose an efficient alternating iterative update algorithm to optimize the proposed model and provide a theoretical analysis of its performance. …”
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PDAM-FAQ: Paraphrasing-Based Data Augmentation and Mixed-Feature Semantic Matching for Low-Resource FAQs by Dongsheng Wang, Liming Wang, Kun Tang, Qile Bo

“…The model extracts keyword features from the text, replacing these keywords with special characters to construct intent features. …”
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Analysis of suspension redundancy performance for frame-type maglev vehicle by LIU Yufei, ZHANG Min, MA Weihua, WANG Aibin

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