Lightweight grading segmentation network for powdery mildew based on model pruning and knowledge distillation by Yuheng Li, Lisha Ye, Yu Zhang, Lijuan Zhou, Qian Chen

“…Our contributions are fourfold: First, we establish a high-performance baseline, PMSeg, which integrates a Mixed Aggregation Network (MANet) and a Channel-wise Cross Fusion Transformer (CCFT) to significantly enhance sensitivity to small targets and multi-scale feature extraction. …”
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Development and validation of a prediction model for VTE risk in gastric and esophageal cancer patients by Xingyue Zheng, Liuyun Wu, Lian Li, Yin Wang, Qinan Yin, Lizhu Han, Xingwei Wu, Yuan Bian

“…Subsequently, a simplified modeling approach was employed using the top 12 feature variables from the best-performing model. …”
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Evolutionary model of heterogeneous clustering wireless sensor networks based on local world theory by Xiu-wen FU, Wen-feng LI

“…,failures of nodes and links) was proposed.Compared with previous research results,the proposed model is closer to reality.By using the mean-field theory,the scale-free feature is demonstrated.Moreover,by studying the impacts of topology growth on error tolerance of the network,it is proved that enlarging the size of the local-world and enhancing the upper limit of de-gree is able to improve the network performance in terms of error-tolerance,while an increase in the cluster proportion and deletion probability led to the degradation of the network error tolerance.…”
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Research on multimodal social media information popularity prediction based on large language model by WANG Jie, WANG Zitong, PENG Yan, HAO Bowen

“…To address the limitations of strong feature dependency, insufficient generalization, and inadequate performance in few-shot/cold-start settings in existing multimodal social media popularity prediction algorithms, a MultiSmpLLM model based on large language model with instruction fine-tuning and human alignment was proposed. …”
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Evolutionary model of heterogeneous clustering wireless sensor networks based on local world theory by Xiu-wen FU, Wen-feng LI

“…,failures of nodes and links) was proposed.Compared with previous research results,the proposed model is closer to reality.By using the mean-field theory,the scale-free feature is demonstrated.Moreover,by studying the impacts of topology growth on error tolerance of the network,it is proved that enlarging the size of the local-world and enhancing the upper limit of de-gree is able to improve the network performance in terms of error-tolerance,while an increase in the cluster proportion and deletion probability led to the degradation of the network error tolerance.…”
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Modeling of laser beam absorption on rough surfaces, powder beds and sparse powder layers by Giandomenico Lupo, Martin Niemann, Christoph Goniva, Wojciech Szmyt, Xiao Jia, Vladyslav Turlo

“…We propose two models capable of predicting this energy transfer, applicable in different scenarios. …”
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The comparative study of machine learning agent models in flood forecasting for tidal river reaches by Ju Zhou, Liming Chen, Tengfei Hu, Hao Lu, Yong Shi, Liangang Chen

“…However, the SVM model performs poorly under extreme flood-tide conditions. …”
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Predicting Nottingham grade in breast cancer digital pathology using a foundation model by Jun Seo Kim, Jeong Hoon Lee, Yousung Yeon, Doyeon An, Seok Jun Kim, Myung-Giun Noh, Suehyun Lee

“…Results The best-performing model achieved an F1 score of 0.731 and a multiclass average AUC of 0.835. …”
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Interpretable machine learning model for predicting post-hepatectomy liver failure in hepatocellular carcinoma by Tianzhi Tang, Tianyu Guo, Bo Zhu, Qihui Tian, Yang Wu, Yefu Liu

“…Variable selection was performed using the least absolute shrinkage and selection operator regression in conjunction with random forest and recursive feature elimination (RF-RFE) algorithms. …”
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Inflammation-nutrition biomarker model for survival prediction in lung cancer patients with concurrent tuberculosis by Hongqi Zhou, Zihao Zhao, Jinhai Wang, Weiyun Jin, Bensong Xian, Lindi Li, XiangWen Nie, WeiWei Wu, Ran Chen, QiZhen Xie, HaiXia Wu, WeiWei Jiang, Min Tang, YuXin Li

“…Eight inflammation-nutrition markers (NLR, PLR, SII, LMR, PNI, HALP, HRR, ALB/GLB) were chosen as predictors while overall survival (OS) was the major event. Feature selection was implemented by LASSO regression; a Cox proportional hazards model was established afterwards. …”
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A Multi-kernel CNN model with attention mechanism for classification of citrus plants diseases by Shiny R M, Angelin Gladston, Khanna Nehemiah H

“…The test accuracy results shows that our model surpasses the other models in terms of its classification performance.…”
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A study on subcutaneous infection model of colibacillosis in broilers: Selected immunological and hematological aspects by Z. Ghahramani, N. Mosleh, T. Shomali, S. Nazifi, A. Khodakaram-Tafti

“…It seems that detection of changes in serum cytokine levels (IL-6, IL-10, and IFN-γ) should be performed in earlier hours of the disease in this model.…”
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Small target detection in UAV view based on improved YOLOv8 algorithm by Xiaoli Zhang, Guocai Zuo

“…This change maintains the model’s performance while significantly reducing the computational load. …”
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Development of a data-driven neural network model for electron thermal transport in NSTX by H. Chung, C.Y. Lee, G.J. Choi, S.M. Kaye, B.P. LeBlanc, J.W. Berkery, Y.-S. Na

“…The model incorporates both convolutional NNs and recurrent NNs, allowing it to simultaneously account for the spatial and temporal non-localities and multi-scale features of turbulent transport, which have been considered only in a limited manner in conventional models. …”
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Identified a novel prognostic model of HCC basing on virus signature for guiding immunotherapy by Shizhuan Huang, Dehai Wu, Guanqun Liao, Ming Liang, Yaohui Zhang, Haotian Wu, Daowei Tang, Dixiang Wen, Bo Jiang, Shan Yu, Sheng Tai

“…Microbiome and RNA sequencing data and clinical information were obtained from The Cancer Genome Atlas, and viruses with prognostic value were identified (Deltabaculovirus, Sicinivirus, and Cytomegalovirus) to construct the prognostic model. Correlation analyses were performed to evaluate the predictive function of the viral signature. …”
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Metal surface defect detection using SLF-YOLO enhanced YOLOv8 model by Yuan Liu, Yilong Liu, Xiaoyan Guo, Xi Ling, Qingyi Geng

“…The key innovations of SLF-YOLO include a novel SC_C2f module with a channel gating mechanism to enhance feature representation and regulate information flow, and a newly designed Light-SSF_Neck structure to improve multi-scale feature fusion and morphological feature extraction. …”
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Hygienic substantiation of calculating models for prognosis of toxicity of different classes insecticides (second part) by O.P. Vavrinevych, B.I. Shpak, A.M. Antonenko, S.T. Omelchuk, T.I. Zinchenko

“…On the basis of a comparison of the toxicometry parameters obtained experimentally (actual parameters) and calculated according to the proposed equations checking of possibility of using of the calculating models for predicting the danger of the investigated groups of insecticides was performed. …”
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Deep neural networks for endemic measles dynamics: Comparative analysis and integration with mechanistic models. by Wyatt G Madden, Wei Jin, Benjamin Lopman, Andreas Zufle, Benjamin Dalziel, C Jessica E Metcalf, Bryan T Grenfell, Max S Y Lau

“…In this paper, we first develop a high-dimensional feed-forward neural network model with spatial features (SFNN) to forecast endemic measles outbreaks and systematically compare its predictive power with that of a classical mechanistic model (TSIR). …”
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Leveraging pretrained deep protein language model to predict peptide collision cross section by Ayano Nakai-Kasai, Kosuke Ogata, Yasushi Ishihama, Toshiyuki Tanaka

“…While the conventional prediction model requires training from scratch, the proposed model enables training with less amount of time owing to the use of the pretrained model as a feature extractor. …”
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Predicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework by Ruize Gao, Shaoze Cui, Yu Wang, Wei Xu

“…A comparative analysis of AUC values further reveals that FinMHSPE outperforms state-of-the-art approaches that rely on financial features as inputs. Furthermore, our investigation identifies several valuable features for enhancing FDP model performance, notably those associated with a company’s information and growth potential.…”
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