EEG-Driven Arm Movement Decoding: Combining Connectivity and Amplitude Features for Enhanced Brain–Computer Interface Performance by Hamidreza Darvishi, Ahmadreza Mohammadi, Mohammad Hossein Maghami, Meysam Sadeghi, Mohamad Sawan

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Integrating Viewing Direction and Image Features for Robust Multi-View Multi-Object 3D Pedestrian Tracking by R. Ali, M. Mehltretter, C. Heipke

“…For each image, this directional information is combined with the 2D features extracted from that image, before 3D features are computed, using the 2D features from all images. …”
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«OLD WOMAN IN VERY MODERN INTERNATIONAL DRESS» (GERMAN DUAL SYSTEM OF VET IN GERMANY AND IN THE WORLD) by Dr. Kress Hannelore, Ekaterina Y. Esenina

“…The purpose of authors – the colleagues cooperating within the Russian-German working group on vocational education – is to determine features of the German dual system of vocational education and training (VET) which make it effective and popular not only in Germany, but also in the world.Methods. …”
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Monopulse Feature Extraction and Fault Diagnosis Method of Rolling Bearing under Low-Speed and Heavy-Load Conditions by Chang Liu, Gang Cheng, Xihui Chen, Yong Li

“…According to the rolling bearing local fault vibration mechanism, a monopulse feature extraction and fault diagnosis method of rolling bearing under low-speed and heavy-load conditions based on phase scan and CNN is proposed. …”
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Text mining approach for feature extraction and cartilage disease grade classification using knee MRI radiology reports by Antonio Saverio Valente, Teresa Angela Trunfio, Marco Aiello, Dario Baldi, Marilena Baldi, Silvio Imbò, Mario Alessandro Russo, Carlo Cavaliere, Monica Franzese

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Features of using artificial intelligence technologies in the self-education activities of academic and pedagogical staff in higher education institutions by Samko Alla

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Enhancing classification of active and non-active lesions in multiple sclerosis: machine learning models and feature selection techniques by Atefeh Rostami, Mostafa Robatjazi, Amir Dareyni, Ali Ramezan Ghorbani, Omid Ganji, Mahdiye Siyami, Amir Reza Raoofi

“…Abstract Introduction Gadolinium-based T1-weighted MRI sequence is the gold standard for the detection of active multiple sclerosis (MS) lesions. …”
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Heart Sound Classification Using Harmonic and Percussive Spectral Features from Phonocardiograms with a Deep ANN Approach by Anupinder Singh, Vinay Arora, Mandeep Singh

“…These results underscore the effectiveness of harmonic-based features and the robustness of the ANN in heart sound classification. …”
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GLTDNet: Cross-Domain Road Extraction Through Collaborative Optimization of Global-Local Feature Enhancement and Topological Decoupling by Jie Chen, Changxian He, Hao Wu, Jun Zhang, Siqiang Rao, Songshan Zhou, Jingru Zhu

“…This approach leverages a hybrid CNN-Transformer architecture and incorporates a global-local feature enhancement unit designed to effectively capture both the intricate local detail features and the overarching global topological structures of roads. …”
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FDRL: a data-driven algorithm for forecasting subsidence velocities in Himalayas using conventional and traditional soil features by Sahil Sankhyan, Ajoy Kumar, Praveen Kumar, Aaditya Sharma, K. V. Uday, Varun Dutt

“…The FDRL model outperformed baseline regression models with a training Root Mean Squared Error (RMSE) of 1.11 mm/year and a test RMSE of 1.32 mm/year. …”
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Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients by Yong Si, Armin Abdollahi, Negin Ashrafi, Greg Placencia, Elham Pishgar, Kamiar Alaei, Maryam Pishgar

“…Initially, 35 features were identified based on expert opinion and a comprehensive literature review; the integrated results of the feature selection methods reduced the feature set to 14. …”
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Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction by Amun Jarzembski, Siddharth Nair, Wyatt Hodges, Matthew Jordan, Anthony McDonald, Logan Antiporda, Greg W. Pickrell, Timothy Walsh, Fabio Semperlotti, Jason Neely, Luke Yates

“…Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. …”
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Radiomic features at contrast-enhanced CT predict proliferative hepatocellular carcinoma and its prognosis after transarterial chemoembolization by Haifeng He, Zhichao Feng, Junhong Duan, Wenzhi Deng, Zuowei Wu, Yizi He, Qi Liang, Yongzhi Xie

“…The radiomics model comprising 9 radiomic features and exhibited good performance for predicting proliferative HCCs. …”
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Comparing supervised classification algorithm–feature combinations for Spartina alterniflora extraction: a case study in Zhanjiang, China by Qiujie Chen, Qiujie Chen, Chunyan Shen, Hong Du, Danling Tang

“…The most accurate algorithm–feature combination was MLC plus spectral features, which achieved a kappa coefficient of 0.9061, an overall accuracy of 95.32%, and a similar extracted area (72.51 ha) to that derived from visual interpretation (68.7 ha). …”
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Radiomics models to predict axillary lymph node metastasis in breast cancer and analysis of the biological significance of radiomic features by Xinhua Li, Minping Hong, Zhendong Lu, Zilin Liu, Lifu Lin, Hongfa Xu

“…ObjectivesTo explore the effectiveness of radiomics in predicting axillary lymph node metastasis (ALNM) and the relationship between radiomics features and genes.MethodThe 379 patients with breast cancer (186 ALNM-positive and 193 ALNM-negative) recruited from three hospitals were divided into the training (n=224), testing (n=96), and validation (n=59) cohorts. …”
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Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer by Weihua Tang, Huadong Chen, Peijun Liu, Yunxuan Zhang, Yunxuan Zhang

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Identification of lethality-related m7G methylation modification patterns and the regulatory features of immune microenvironment in sepsis by Dan Wang, Rujie Huo, Lu Ye

“…This study aimed to explore the patterns of lethality-related m7G regulatory factor-mediated RNA methylation modification and immune microenvironment regulatory features in sepsis. Methods: Three sepsis-related datasets (E-MTAB-4421 and E-MTAB-4451 as training sets and GSE185263 as a validation set) were collected, and differentially expressed m7G-related genes were analyzed between survivors and non-survivors. …”
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‘Machine Learning’ multiclassification for stage diagnosis of Alzheimer’s disease utilizing augmented blood gene expression and feature fusion by Manash Sarma, Subarna Chatterjee

“…Because of high data imbalance in genomic data, border line oversampling is explored for model training and original data for validation. We have conducted a multimodal analysis and stage classification by integrating the ADNI gene expression and clinical datasets using ‘Feature-Level Fusion’. …”
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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

“…This paper proposes a method based on explainable artificial intelligence feature selection and machine learning to detect pests and beneficial insects in field crops. …”
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A Novel Detection Scheme for Motor Bearing Structure Defects in a High-Speed Train Using Stator Current by Qi Sun, Juan Zhu, Chunjun Chen

“…Railway traction motor bearings (RTMB) are critical components in high-speed trains (HST) that are particularly susceptible to failure due to the high stress and rotational frequency they experience. …”
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