Visual Classification of Music Style Transfer Based on PSO-BP Rating Prediction Model by Tianjiao Li

“…At the same time, we take advantage of the BP neural network’s ability to handle complex nonlinear problems and construct a rating prediction model between the user and item attribute features, referred to as the PSO-BP rating prediction model, by combining the features of global optimization of particle swarm optimization algorithm, and make further improvements based on the traditional collaborative filtering algorithm.…”
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A transcriptome-based risk model in sepsis enables prognostic prediction and drug repositioning by Qiuyue Long, Hongli Ye, Shixu Song, Jiwei Li, Jing Wu, Jingsong Mao, Ran Li, Ke Li, Zhancheng Gao, Yali Zheng

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Development, validation and recalibration of a prediction model for prediabetes: an EHR and NHANES-based study by Nicholas J. Casacchia, Kristin M. Lenoir, Joseph Rigdon, Brian J. Wells

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Characterization of pathogenic microorganisms in diabetic foot infections and development of a risk prediction model by Shufang Yan, Xuemeng Zhu, Tong Yu, Dandan Li, Su Li, Lei Xue

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ORF1ab codon frequency model predicts host-pathogen relationship in orthocoronavirinae by Phillip E. Davis, Joseph A. Russell

“…Here, we focus narrowly on the Orthocoronavirinae clade and demonstrate models that are powerfully predictive for a human-pathogen phenotype with 76.74% average precision and 85.96% average recall on the withheld test set groups, using only Orf1ab codon frequencies. …”
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Predicting Freeway Work Zone Delays and Costs with a Hybrid Machine-Learning Model by Bo Du, Steven Chien, Joyoung Lee, Lazar Spasovic

“…A hybrid machine-learning model, integrating an artificial neural network (ANN) and a support vector machine (SVM) model, is developed to predict spatiotemporal delays, subject to road geometry, number of lane closures, and work zone duration in different periods of a day and in the days of a week. …”
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“AFLA-peanut”, a mechanistic prototype model to predict aflatoxin B1 contamination by Matteo CROSTA, Marco CAMARDO LEGGIERI, Paola BATTILANI

“…A mechanistic weather-driven prototype model to predict AFB1 contamination in peanuts was developed by adapting the mechanistic AFLA-maize model for the Aspergillus flavus-peanut pathosystem. …”
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A prediction tool for plaque progression based on patient-specific multi-physical modeling. by Jichao Pan, Yan Cai, Liang Wang, Akiko Maehara, Gary S Mintz, Dalin Tang, Zhiyong Li

“…Atherosclerotic plaque rupture is responsible for a majority of acute vascular syndromes and this study aims to develop a prediction tool for plaque progression and rupture. …”
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Creep behavior of clayey soil and its model prediction in the Cangzhou land subsidence area by Jianfeng Qi, Yongjie Xie, Chen Li, Haipeng Guo, Yunlong Wang

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Artificial intelligence-based metabolic energy prediction model for animal feed proportioning optimization by Hehua Wang, Jinhai Liu, Ziyu Dong, Jingnan Song, Zhaoyu Zhu

“…It suggests that the model designed can better predict metabolic energy. …”
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A Dynamic Spatio-Temporal Deep Learning Model for Lane-Level Traffic Prediction by Bao Li, Quan Yang, Jianjiang Chen, Dongjin Yu, Dongjing Wang, Feng Wan

“…In this paper, we propose a deep learning model for lane-level traffic prediction. Specifically, we take advantage of the graph convolutional network (GCN) with a data-driven adjacent matrix for spatial feature modeling and treat different lanes of the same road segment as different nodes. …”
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Performance of a kinetic model for predicting internal sulphate attack in Portland cement mortars by S.O. Ekolu, J. Dateling, A. Naghizadeh

“…The present study evaluated an existing kinetic model originally proposed for predicting delayed ettringite formation (DEF) in cementitious systems for potential dual employment to predict internal sulphate attack (ISA). …”
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A machine learning model for predicting severity-adjusted in-hospital mortality in pneumonia patients by Jong-Ho Park, Jihye Lim

“…Conclusion These results suggest that further research is needed on models that adjust for the severity of comorbidities for each diagnosis to more accurately predict health outcomes.…”
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Fast prediction of irradiation-induced cascade defects using denoising diffusion probabilistic model by Ruihao Liao, Ke Xu, Yifan Liu, Zibo Gao, Shuo Jin, Linyun Liang, Guang-Hong Lu

“…We propose a computational scheme that combines molecular dynamic (MD) simulations with a denoising diffusion probabilistic model (DDPM) to rapidly and accurately predict the spatial coordinates of point defects at any given primary knock atom (PKA) energy, ranging from 0 to 100.0 keV. …”
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LOGISTIC MODELING TO PREDICT THE INTEREST OF THE INDONESIAN PEOPLE FOR BUYING FLOOD IMPACTED INSURANCE PRODUCTS by Yulial Hikmah

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Analysis of risk factors for sepsis-related liver injury and construction of a prediction model by Yong He, Yong He, Yong He, Chi Wang, Chi Wang, Chi Wang, Wan He, Wan He, Wan He, He Zhang, He Zhang, He Zhang, Fei Ding, Fei Ding, Fei Ding, Ying Liu, Ying Liu, Ying Liu, He He, He He, He He, Binwu Ying, Binwu Ying, Binwu Ying, Xin Nie, Xin Nie, Xin Nie, Xin Nie

“…The area under the curve (AUC) of the predictive model was 0.890, with a sensitivity of 80.0% and a specificity of 82.91%, indicating excellent diagnostic value.ConclusionIn conclusion, this study developed a highly accurate predictive model for SRLI using clinically accessible serum indicators, which could aid in early detection and intervention, potentially reducing mortality rates.…”
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Data-driven deep learning model for predicting ambient temperature: environment and solar energy by Reza Hassanian, Nashmin Yeganeh, Ásdís Helgadóttir, Runar Unnthorsson, Morris Riedel

“…The superiority of the model lies in its accurate predictions using limited data and reasonable computational resources. …”
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The normalization model predicts responses in the human visual cortex during object-based attention by Narges Doostani, Gholam-Ali Hossein-Zadeh, Maryam Vaziri-Pashkam

“…We then determined the observed effects of attention on cortical responses and demonstrated that these effects were predicted by the normalization model, but not by the weighted sum or the weighted average models. …”
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Development of Modified LSTM Model for Reservoir Capacity Prediction in Huanggang Reservoir, Fujian, China by Bibo Dai, Jiangbin Wang, Xiao Gu, Chunyan Xu, Xin Yu, Haosheng Zhang, Canming Yuan, Wen Nie

“…In order to accurately understand the Huanggang Reservoir capacity change, we develop a new hydrological prediction model based on the LSTM (Long-Short-Term Memory) method, which is used to predict the capacity of the reservoir. …”
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Online Purchase Behavior Prediction Model Based on Recurrent Neural Network and Naive Bayes by Chaohui Zhang, Jiyuan Liu, Shichen Zhang

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