Ensemble learning approach for prediction of early complications after radiotherapy for head and neck cancer using CT and MRI radiomic features by Benyamin Khajetash, Seied Rabi Mahdavi, Alireza Nikoofar, Lee Johnson, Meysam Tavakoli

“…The RT and BN models based on $$T_1$$ weighted images show better performance than those obtained with $$T_2$$ weighted images. …”
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Accurate total consumer price index forecasting with data augmentation, multivariate features, and sentiment analysis: A case study in Korea. by Injae Seo, Minkyoung Kim, Jong Wook Kim, Beakcheol Jang

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Lexico-semantic features of Kara-Nogais talk of the Mikhailovsk city, Stavropol Territory (by the linguistic expedition materials of NRU SSPI 2023) by Artyom S. Goncharov, Olesya S. Makarova, Inna I. Lizenko

“…It is concluded that morphologically, the Kara-Nogais dialect is agglutinative, parts of speech are divided into names, verbs and auxiliary parts of speech; the semantics of the dialect testifies to the extreme closeness of the society of the Kara-Nogais, who developed their own model of the world and the peculiarities of the hermeneutics of natural, social and cultural processes in the framework of life, speech creativity and performance of singing traditions, sayings, riddles.…”
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Multilevel Feature Gated Fusion Based Spatial and Frequency Domain Attention Network for Joint Classification of Hyperspectral and LiDAR Data by Cuiping Shi, Zhipeng Zhong, Shihang Ding, Yeqi Lei, Liguo Wang, Zhan Jin

“…In addition, most existing joint classification methods based on attention and transformer only perform global modeling in the spatial domain, ignoring the sensitivity of the frequency domain to fine features. …”
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Multi-Level Feature Fusion in CNN-Based Human Action Recognition: A Case Study on EfficientNet-B7 by Pitiwat Lueangwitchajaroen, Sitapa Watcharapinchai, Worawit Tepsan, Sorn Sooksatra

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Uncovering the Diagnostic Power of Radiomic Feature Significance in Automated Lung Cancer Detection: An Integrative Analysis of Texture, Shape, and Intensity Contributions by Sotiris Raptis, Christos Ilioudis, Kiki Theodorou

“…Methods: We developed and compared the performance of two machine learning models—DenseNet-201 CNN and XGBoost—trained on radiomic features with the ability to identify malignant tumors from benign ones. …”
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The Moderating Effect of the Sector's Level of Concentration on the Relationship Between Balance Sheet Composition and the Firm's Competitive Advantage by Luiz Claudio Louzada, Márcio Augusto Gonçalves

“…The test results suggest that (i) the firm’s idiosyncratic features have greater explanatory capability for the firm’s performance than the industry features; (ii) the relation between firm idiosyncratic resources and firm performance are sensitive to industry characteristics.…”
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Distinguishing benign and malignant myxoid soft tissue tumors: Performance of radiomics vs. radiologists. by Joshua M Lawrenz, Can Cui, Samuel R Johnson, Katherine S Hajdu, Stephen W Chenard, Akhil Rekulapelli, Cullen P Moran, John J Block, Nicholson S Chadwick, Joanna L Shechtel, Brian Bingham, Leo Y Luo, Jennifer L Halpern, Herbert S Schwartz, Ginger E Holt, David S Smith, Benoit Dawant, Hakmook Kang

“…<h4>Introduction</h4>Benign and malignant myxoid soft tissue tumors have shared clinical, imaging, and histologic features that can make diagnosis challenging. The purpose of this study is comparison of the diagnostic performance of a radiomic based machine learning (ML) model to musculoskeletal radiologists.…”
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Efficient Dynamic Performance Prediction of Railway Bridges Situated on Small-Radius Reverse Curves by Yumin Song, Bin Hu, Xiaoliang Meng

“…Through supervised training with dynamic performance labels, this process empowers the SVM model to predict the dynamic performance of the bridge. …”
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Integrating ultrasound radiomics and clinicopathological features for machine learning-based survival prediction in patients with nonmetastatic triple-negative breast cancer by Wenwen, Zekun Jiang, Jingyan Liu, Dingbang Liu, Yiyue Li, Yushuang He, Haina Zhao, Lin Ma, Yixin Zhu, Qiongxian Long, Jun Gao, Honghao Luo, Heng Jiang, Kang Li, Xiaorong Zhong, Yulan Peng

“…Abstract Objective This study aimed to evaluate the predictive value of implementing machine learning models based on ultrasound radiomics and clinicopathological features in the survival analysis of triple-negative breast cancer (TNBC) patients. …”
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Differentiation between multiple sclerosis and neuromyelitis optic spectrum disorders with multilevel fMRI features: A machine learning analysis by Xiao Liang, Qingwen Zeng, Yanyan Zhu, Yao Wang, Ting He, Lin Wu, Muhua Huang, Fuqing Zhou

“…Adding structural features of gray matter volume (GMV) data did not notably improve the classification performance of the machine learning models using multilevel rs-fMRI features. …”
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Discrimination of Chinese prickly ash origin place using electronic nose system and feature extraction with support vector boosting machine by Junbo Lian, Peng Wu, Wenhui Han, Yaping Xie, Yue Zheng, Yuxuan Xu, Xinlin Li, Guofeng Hou, Chengxiang Yong, Qi Lv, Qiansheng Ye, Guohua Hui

“…Empirical results demonstrate the superior performance of the model, achieving an impressive accuracy of 95.17% when retaining five features per sensor. …”
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Neural signatures of depression: classifying drug-naïve MDD patients with time- and frequency-domain EEG features during emotional processing by Bernis Sütçübaşı, Tuğçe Ballı, Barış Metin, Emine Elif Tülay

“…The mean power amplitudes of event-related potentials (ERP), including the P200, P300, early, middle, and late components of the late positive potential (LPP), were computed, along with band power features, and used as features for classifiers. A support vector machine model was employed for classification to evaluate the individual contributions of ERP components and band power features and explore the combined effects of ERP components and band power features within themselves. …”
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AI may help to predict thyroid nodule malignancy based on radiomics features from [18F]FDG PET/CT by Krystian Ślusarz, Mikolaj Buchwald, Adrian Szczeszek, Szymon Kupinski, Anna Gramek-Jedwabna, Wojciech Andrzejewski, Juliusz Pukacki, Robert Pękal, Marek Ruchała, Rafał Czepczyński, Cezary Mazurek

“…Of these 50 patients, 11 (22.0%) [18F]FDG-avid nodules were diagnosed as malignant. The performance of the XGBoost model in assessing [18F]FDG-avid TI was similar (0.846 [confidence interval, CI, 95% 0.737–0.956]) to SUVmax (0.797 [CI 95%: 0.622–0.973]; p = 0.60). …”
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Automatic Non-Urban Road Surface Point Extraction Based on Geometric Features Using Neural Networks and Raster Structure Approach by M. Dowajy, M. Fawzy, M. Fawzy, A. Barsi, T. Lovas

“…The features are projected onto a regular grid and converted into a raster format where each pixel's value represents the averaged features of points within its space. …”
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ML-based top taggers: Performance, uncertainty and impact of tower & tracker data integration by Rameswar Sahu, Kirtiman Ghosh

“…Machine learning algorithms have the capacity to discern intricate features directly from raw data. We demonstrated the performance of top taggers built upon three machine learning architectures: a BDT that uses jet-level variables (high-level features, HLF) as input, a CNN (a miniature version of ResNet) trained on the jet image, and a GNN (LorentzNet) trained on the particle cloud representation of a jet utilizing the 4-momentum (low-level features, LLF) of the jet constituents as input. …”
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COVID-19 Severity Classification Using Hybrid Feature Extraction: Integrating Persistent Homology, Convolutional Neural Networks and Vision Transformers by Redet Assefa, Adane Mamuye, Marco Piangerelli

“…By integrating features from both methods, the classification model effectively predicted severity levels (mild, moderate, severe). …”
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Robust scale fusion and edge-aware feature attention network for remote sensing UAV road detection under harsh weather by Jialang Liu, Jialei Zhan, Jiehua Zhang, Jiangming Chen, Yan Song, Lixing Tang, Le Zhou, Chengsi Du, Yingmei Wei, Yanming Guo

“…To support evaluation under realistic conditions, we construct a dedicated UAV-based road inspection dataset comprising 19,832 images collected across diverse weather scenarios such as rain, snow, and fog. This dataset features fine-grained annotations and provides a valuable benchmark for assessing detection performance in adverse environments. …”
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Performance Evaluation of Hybrid Machine Learning Algorithms for Online Lending Credit Risk Prediction by Tesfahun Berhane, Tamiru Melese, Abdu Mohammed Seid

“…The experimental results show that the hybrid CNN-kNN model outperforms the CNN-GBDT and CNN-LR models based on the performance metrics accuracy, recall, F1-score, and area under the curve for both all input and important features. …”
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Analysis of propagation and coverage performance of indoor single-carrier radio signals in the terahertz bands by Mugen PENG, Chuang YANG, Tianhang ZHOU

“…To tackle the problem that radio signal in the terahertz band had different features compared to that in the conventional spectrum, which restricted its application to indoor communication scenarios, a modified propagation model of terahertz radio signal was proposed.Based on the model, the propagation and coverage performances of wide-band single-carrier terahertz radio signal were analyzed.In particular, the wide-band terahertz channel transfer function was constructed, taking the absorption loss introduced by the thickness of the obstacles into account.Using the ray tracing technique, the impacts of the obstacles’ thickness and the bandwidth on the propagation and coverage performances were examined, showing that the coverage performance can be improved by leveraging the reflections from the non-line-of-sight obstacles.Moreover, the trade-off between the coverage radius and the capacity of terahertz communications is revealed, and it is further found that the theoretical spectral efficiency decreases as the carrier frequency of terahertz radio signal increases.…”
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