Joint event extraction model based on dynamic attention matching and graph attention networks by Jiajun Cheng, Wenjie Liu, Zhifan Wang, Zhijie Ren, Xingwen Li

“…Experiment results on the ACE2005 dataset demonstrate that our proposed model attains competitive performance in comparison to existing methods.…”
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AMFGNN: an adaptive multi-view fusion graph neural network model for drug prediction by Fang He, Fang He, Fang He, Fang He, Lian Duan, Lian Duan, Lian Duan, Lian Duan, Guodong Xing, Guodong Xing, Guodong Xing, Guodong Xing, Xiaojing Chang, Xiaojing Chang, Xiaojing Chang, Xiaojing Chang, Huixia Zhou, Huixia Zhou, Huixia Zhou, Huixia Zhou, Mengnan Yu, Mengnan Yu, Mengnan Yu, Mengnan Yu

“…Furthermore, a Kolmogorov-Arnold network is employed to perform weighted fusion of various final features, optimizing prediction performance.ResultsAMFGNN demonstrates a significant advantage in predictive performance, achieving an average AUC value of 0.9453, which reflects the model‘s high accuracy in prediction.DiscussionCross-validation results across multiple datasets indicate that AMFGNN outperforms seven advanced drug-disease association prediction methods. …”
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Short-Term Load Forecasting in Power Systems Based on the Prophet–BO–XGBoost Model by Shuang Zeng, Chang Liu, Heng Zhang, Baoqun Zhang, Yutong Zhao

“…This approach employs the XGBoost model to interpret the nonlinear relationships between features and loads and integrates the Prophet model for label prediction from a time-series viewpoint. …”
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Development and Validation of a Clinical Risk Model for Predicting Malignancy in Patients with Thyroid Nodules by Shiva Borzouei, Ali Safdari, Erfan Ayubi

“…The AUC and Brier score of the model were 0.89 and 0.12, respectively. The DCA also showed that the model performed well in clinical practice. …”
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Evolving Hybrid Deep Neural Network Models for End-to-End Inventory Ordering Decisions by Thais de Castro Moraes, Jiancheng Qin, Xue-Ming Yuan, Ek Peng Chew

“…<i>Results:</i> Empirical evaluation of real-world retail data demonstrates that our proposed models proficiently extract pertinent features and interpret sequential data characteristics, leading to more accurate and informed ordering decisions. …”
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High-throughput atomistic modeling of nanocrystalline structure and mechanics of calcium aluminate silicate hydrate by Yunjian Li, Cheng Chen, Zhenning Li, Zongjin Li

“…Here, we present a high-throughput atomistic modeling framework to systematically investigate the structural and mechanical properties of C-A-S-H across a broad range of Ca/Si (1.3–1.9) and Al/Si (0–0.15) ratios. …”
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Comparative analysis of data-driven models for spatially resolved thermometry using emission spectroscopy. by Ruiyuan Kang, Dimitrios C Kyritsis, Panos Liatsis

“…In total, combinations of fifteen feature groups and fifteen classical machine learning models, and eleven CNN models are considered and their performances explored. …”
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Development of the Optuna-NGBoost-SHAP model for estimating ground settlement during tunnel excavation by Yuxin Chen, Mohammad Hossein Kadkhodaei, Jian Zhou

“…This study aims to develop and evaluate a natural gradient boosting (NGBoost) model optimized with Optuna for estimating ground settlement during tunnel excavation, incorporating Shapley additive explanations (SHAP) to perform interpretability analysis on the model’s estimation results. …”
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Research on Traffic Accident Severity Level Prediction Model Based on Improved Machine Learning by Jiming Tang, Yao Huang, Dingli Liu, Liuyuan Xiong, Rongwei Bu

“…The analysis results show that the improved machine learning model is significantly superior to a single model in the overall performance. …”
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Preliminary investigation on predicting postoperative glioma recurrences based on a multiparametric radiomics model by Fang-Xiong Fu, Fang-Xiong Fu, Guo Li, Lan Hong, Wang-Sheng Chen

“…This study aimed to evaluate the performance of a magnetic resonance imaging (MRI)-based multiparametric radiomics model for the early prediction of postoperative recurrences.MethodsThe data from 60 patients who met the inclusion criteria between 2000 and 2021 were collected in this study. …”
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Heart Failure Prediction Based on Bootstrap Sampling and Weighted Fusion LightGBM Model by Yuanni Wang, Hong Cao

“…Compared with the traditional prediction model, the model shows better comprehensive performance in terms of various performance metrics such as accuracy, precision, recall, and F1 score, and also performs better in the paired <i>t</i>-test. …”
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SGM-EMA: Speech Enhancement Method Score-Based Diffusion Model and EMA Mechanism by Yuezhou Wu, Zhiri Li, Hua Huang

“…The score-based diffusion model has made significant progress in the field of computer vision, surpassing the performance of generative models, such as variational autoencoders, and has been extended to applications such as speech enhancement and recognition. …”
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A New Pes Planus Automatic Diagnosis Method: ViT-OELM Hybrid Modeling by Derya Avcı

“…The suggested ViT-OELM hybrid model includes an attention mechanism for feature extraction from the pes planus images. …”
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Prediction models for cognitive impairment in middle-aged patients with cerebral small vessel disease by Wei Zheng, Xiaoyan Qin, Ronghua Mu, Peng Yang, Bingqin Huang, Bingqin Huang, Zhixuan Song, Xiqi Zhu, Xiqi Zhu

“…This study also included the extraction of total intracranial volume, gray matter, white matter, cerebrospinal fluid, white matter hypertensit, and hippocampus volume. The performance of the models was assessed using the areas under the receiver operating characteristic curves (AUCs). …”
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Research on Oil Well Production Prediction Based on GRU-KAN Model Optimized by PSO by Bo Qiu, Jian Zhang, Yun Yang, Guangyuan Qin, Zhongyi Zhou, Cunrui Ying

“…The Pearson correlation coefficient is used to select the most significant features. These selected features are used as input to the GRU-KAN model to establish the oil well production prediction model. …”
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A Hierarchical RF-XGBoost Model for Short-Cycle Agricultural Product Sales Forecasting by Jiawen Li, Binfan Lin, Peixian Wang, Yanmei Chen, Xianxian Zeng, Xin Liu, Rongjun Chen

“…Additionally, its generalization is validated across 42 types of agricultural products from six vegetable categories, showing its extensive practical ability. Such performances reveal that the proposed model beneficially enhances the precision of short-term agricultural product sales forecasting, with the advantages of optimizing the supply chain from producers to consumers and minimizing food waste accordingly.…”
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GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity by Junwei Luo, Ziguang Zhu, Zhenhan Xu, Chuanle Xiao, Jingjing Wei, Jiquan Shen

“…Then GATv2-GCN and the three-layer GCN networks are used to extract the features of the drug. GATv2-GCN enhances the model’s ability to focus on important nodes by assigning dynamic attention scores, which improves the learning of the graph structure’s intricate patterns. …”
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Mathematical Modeling for Ceramic Shape 3D Image Based on Deep Learning Algorithm by Lijian Zhang, Guangfu Liu

“…The experimental results show that the proposed 3D image modeling method has significant advantages in compression performance compared with the optimal 2D 3D image modeling method based on deep learning, and the experimental results show that the performance of the proposed method is superior to JP3D and HEVC methods, especially at low bit rate points.…”
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Assessing BERT-based models for Arabic and low-resource languages in crime text classification by Njood K. Al-harbi, Manal Alghieth

“…The study evaluates these models’ performance in comparison to machine learning (ML), deep learning (DL), and other Transformer models. …”
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Data-driven modeling of environmental factors influencing Arctic methanesulfonic acid aerosol concentrations by J. B. Pernov, J. B. Pernov, W. H. Aeberhard, M. Volpi, E. Harris, E. Harris, B. Hohermuth, S. Ishino, R. B. Skeie, S. Henne, U. Im, P. K. Quinn, L. M. Upchurch, L. M. Upchurch, J. Schmale

“…Although the overall performance of our data-driven models on test data is modest (max. …”
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