Improved integral neural distinguisher model for lightweight cipher PRESENT by Wanqing Wu, Mingyu Guo

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Large language models as a diagnostic support tool in neuropathology by Katherine J Hewitt, Isabella C Wiest, Zunamys I Carrero, Laura Bejan, Thomas O Millner, Sebastian Brandner, Jakob Nikolas Kather

“…Large language models (LLMs) have demonstrated their ability to parse and process complex medical text, but their utility in neuro‐oncology has not been systematically tested. …”
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Geoelectrical Models of Glacial-Permafrost Rock Formations of the Central Altai by G. S. Dyakova, A. A. Goreyavcheva, A. N. Shein, V. V. Potapov, R. D. Burym, O. V. Ostanin, V. V. Olenchenko

“…When analyzing the three-dimensional model of the GPRF, it is clearly noticeable that the features of the nature of the SER distribution reflects the inhomogeneous distribution of ice within the rock-ice core of the GPRF. …”
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Landslide Susceptibility Assessment Using the Geographical-Optimal-Similarity Model by Yonghong Xiao, Guolong Li, Lu Wei, Jing Ding, Zhen Zhang

“…This research used 11 remote sensing feature factors and 657 historical landslide points, combined with the IV model, to construct a dataset for landslide prediction and susceptibility assessment using the GOS model. …”
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The Smart Product Backlog: A Classification Model of User Stories by Mauricio Gaona-Cuevas, Victor Bucheli Guerrero, Fredy H. Vera-Rivera

“…This model had leveraged advanced text processing techniques to refine the textual features of the US. …”
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Explainable machine learning-driven models for predicting Parkinson’s disease and its prognosis: obesity patterns associations and models development using NHANES 1999–2018 data... by Jiaxin Fan, Shuai Cao, Hang Peng, Yuanjie Zhi, Shuqin Zhan, Rui Li

“…LASSO + RF identified eight features, achieving moderate performance in PD prediction (SMOTE set: AUCROC = 0.75, Brier = 0.20) and prognosis (train set: AUCROC = 0.72, Brier = 0.22) nomograms, with similar results in the test set (AUCROC = 0.70, Brier = 0.01 for prediction, 0.87 and 0.18 for prognosis). …”
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Flood Susceptibility Mapping in Ghare Ghom watershed by Sima Pourhashemi, Kazem Aliabadi

“…Model performance was evaluated using the Area Under the ROC Curve (AUC) and the Tolerance Index.Findings: The RF model results show that distance from the river, rainfall, and altitude had the greatest impact on flood sensitivity. …”
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Vehicle detection and classification for traffic management and autonomous systems using YOLOv10 by Anning Ji, Xintao Ma

“…We propose a novel detection framework, YDFNet, that integrates the YOLOv10 algorithm for fast feature extraction, the BiFPN (Bidirectional Feature Pyramid Network) for multi-scale feature fusion, and the DETR (Detection Transformer) architecture for global feature modeling. …”
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Falling Detection of Toddlers Based on Improved YOLOv8 Models by Ziqian Yang, Baiyu Tsui, Jiachuan Ning, Zhihui Wu

“…The procedure is executed in two stages: In stage I, a GELAN-integrated YOLOv8 model is used to extract the body features. Based on this, a head capture technique is developed to obtain the head features. …”
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NEURAL NETWORK MODEL OF DIAGNOSTICS OF STAGES OF DEVELOPING CORPORATE BANKRUPTCY by S. A. Gorbatkov, S. A. Farkhieva

“…New features of the method, increasing the predictive power of the model, are: 1) optimal selection of factors using Bayesian ensemble of auxiliary neural networks, performing compression of factor space; 2) step compression of factors based on the generalized Harrington desirability function; 3) regularization of the main (working) neural network model on Bayesian ensemble of neural networks. …”
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Specialized Large Language Model for Standardization of Locomotive Maintenance Data by CHEN Ao, LI Chen, YAN Jiayun, PENG Liantie, TIAN Ye, LIU Leixinyuan

“…However, traditional manual methods encounter challenges such as small sample sizes, non-standardized data formats, analytical complexities, and high labour costs, hindering the achievement of data standardization. Large language models (LLM), featuring powerful performance in natural language processing comprehension and handling complex tasks, have made great academic and industrial progress in recent years. …”
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Estimating strawberry weight for grading by picking robot with point cloud completion and multimodal fusion network by Yiming Chen, Wei Wang, Junchao Chen, Jizhou Deng, Yuanping Xiang, Bo Qiao, Xinghui Zhu, Changyun Li

“…The results indicate that among traditional machine learning methods, the SVR model achieved the best performance with an accuracy of 77.7% (PCW@0.2). …”
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Fault analysis of chemical equipment based on an improved hybrid model. by Wu Huiyong, Kuan Jiang, Wang Yanyu

“…The pre-activation mechanism introduced in the residual blocks of ResNet improves training efficiency and model stability. Subsequently, the BiGRU model is used to model the extracted features in the time domain, capturing complex temporal dependencies. …”
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Impact of Temporal Resolution on Autocorrelative Features of Cerebral Physiology from Invasive and Non-Invasive Sensors in Acute Traumatic Neural Injury: Insights from the CAHR-TBI... by Nuray Vakitbilir, Rahul Raj, Donald E. G. Griesdale, Mypinder Sekhon, Francis Bernard, Clare Gallagher, Eric P. Thelin, Logan Froese, Kevin Y. Stein, Andreas H. Kramer, Marcel J. H. Aries, Frederick A. Zeiler

“…Findings show that both raw and derived indices exhibit intrinsic ARIMA components regardless of resolution. Ignoring these features risks compromising the significance of models developed from such data. …”
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Venous thromboembolism swine model with reflux-induced venous hypertension by Mengjun Wang, MD, Xiao Lu, PhD, Ling Han, BS, José A. Diaz, MD, Seshadri Raju, MD, Ghassan S. Kassab, PhD

“…Objective: This study describes a novel swine model of venous thromboembolism (VTE) with reflux-induced venous hypertension. …”
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Machine learning models for prognosis prediction in regenerative endodontic procedures by Jing Lu, Qianqian Cai, Kaizhi Chen, Bill Kahler, Jun Yao, Yanjun Zhang, Dali Zheng, Youguang Lu

“…Conclusions RF and GBM models outperformed XGB, logR, SVM models on the overall performance on our datasets, exhibiting the potential capability to predict the prognosis of REPs. …”
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Research on 3D modeling of underground roadways in coal mines by LIAN Boxiang, MI Langtao, LI Shangjie, GUO Jiyao

“…However, in underground environments with sparse geometric features, there exist problems such as insufficient point cloud registration accuracy and low efficiency. …”
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Deep Learning Models for Predicting the Recurrence of Idiopathic Granulomatous Mastitis by Li L, Yang W, Jia H

“…Feature importance analysis indicated that variables such as smoking, surgery and a history of oral contraceptive use were most important in predicting recurrence.Conclusion: This study demonstrates that, compared to logistic regression and random forest models, neural networks have superior performance in predicting the recurrence of granulomatous mastitis. …”
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Opinion mining using ensemble model for restaurant feedback analysis by Rohan S. Kamath, M. R. Kaushik, M. Ramakrishna

“…Models are then trained and evaluated using performance metrics like accuracy, precision, recall, and F1 score. …”
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Deep FS: A Deep Learning Approach for Surface Solar Radiation by Fatih Kihtir, Kasim Oztoprak

“…The proposed Deep-FS model is validated and compared with the traditional approaches and models through the standard performance metrics. …”
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