A framework for predictive modeling of microbiome multi-omics data: latent interacting variable-effects (LIVE) modeling by Javier Munoz Briones, Douglas K. Brubaker

“…Here, we present a framework for integration of microbiome multi-omics data: Latent Interacting Variable Effects (LIVE) modeling. LIVE integrates multi-omics data using single-omic latent variables (LV) organized in a structured meta-model to determine the combinations of features most predictive of a phenotype or condition. …”
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Predicting South African consumers’ intention to continue using their preferred retail bank’s services: A model validation by Marko van Deventer, Kirsty-Lee Sharp, Rafał Żelazny, Sebastian Kot

“…Research Design & Methods: This study focuses on predicting South African consumers’ intention to continue using their preferred retail bank’s services through a validated measurement model. …”
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An interpretable machine learning approach for predicting drug-resistant epilepsy in children with tuberous sclerosis complex by Jie Fu, Jie Fu, Genfu Zhang, Genfu Zhang, Zhixian Yang, Zhixian Yang, Jiong Qin, Jiong Qin

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Validation of a Finite Element Simulation for Predicting Individual Knee Joint Kinematics by Elin Theilen, Anna Rorich, Thomas Lange, Sebastian Bendak, Cora Huber, Hagen Schmal, Kaywan Izadpanah, Joachim Georgii

Subjects: “…Finite element knee joint model…”
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Prediction for Acute Biliary Pancreatitis After Laparoscopic Cholecystectomy by Yue D, Hu S

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Terrain Simplification Algorithm in Radio Wave Propagation Prediction by Dan Shi, Zhen Zhang, Fengshuo Wei, Cheng Lian

“…In order to study the influence of terrain simplification on the prediction of complex electromagnetic environment, a visibility algorithm used in the regular model of terrain and a probability-based power propagation model are proposed. …”
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Machine Learning Methods as a Tool for Analysis and Prediction of Impact Resistance of Rubber–Textile Conveyor Belts by Miriam Andrejiova, Anna Grincova, Daniela Marasova, Zuzana Kimakova

“…Based on the data obtained from the design properties of conveyor belts and experimental testing conditions, four models were created (regression model, decision tree regression model, random forest model, ANN model), which are used to analyze and predict the impact force of the force acting on the conveyor belt during material impact. …”
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COMPUTER SCIENCE, COMPUTER ENGINEERING AND MANAGEMENT SYNTHESISING THE MODEL OF THE PREDICTIVE MAINTENANCE OF ATMOSPHERIC PIPE STILL by E. S. Gebel, A. A. Ibatullin, M. S. Peshko, V. N. Gudinov

“…The aim of the study is to develop a model of a predictive maintenance system allowing the output parameters of a high-capacity distillation unit to be stabilised.Method. …”
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Prediction of Heat Transfer For Turbulent Flow in Rotating Radial Duct by P. Tekriwal

“…The objective of the current modeling effort is to validate the numerical model and improve upon the prediction of heat transfer in rotating systems. …”
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An Online Interactive Experiment Management System for CMA Numerical Weather Prediction Models by Wang Bin, Hu Jiangkai, Cui Yingjie, Zhou Bin, Sun Jing, Zhao Chunyan, Lou Panxing

Subjects: “…numerical weather prediction model…”
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Predictable motorway ramp curves are safer by Johan Vos

“…Applying this research to motorway design involves using TAN predictions and crash frequency models to assess safety in motorway curve design, which could proactively improve road safety.…”
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Research on E-Commerce Inventory Sales Forecasting Model Based on ARIMA and LSTM Algorithm by Chenyang Wang, Junsheng Wang

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Models based on dietary nutrients predicting all-cause and cardiovascular mortality in people with diabetes by Fang Wang, Yukang Mao, Jinyu Sun, Jiaming Yang, Li Xiao, Qingxia Huang, Chenchen Wei, Zhongshan Gou, Kerui Zhang

“…The study aims to establish models predicting long-term mortality and explore dietary nutrients associated with reduced long-term events to guide daily dietary decisions in people with DM. …”
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Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation by Wanli Xiong, Qiqi Cao, Lu Jia, Min Chen, Tao Liu, Qingyan Zhao, Yanhong Tang, Bo Yang, Li Li, Shaobo Shi, He Huang, Congxin Huang, China Atrial Fibrillation Center Project Team

“…Conclusion This simplified prediction model effectively identifies the risk of LAT in patients with paroxysmal AF, providing a valuable tool for clinical decision-making. …”
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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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A novel deep learning model for predicting marine pollution for sustainable ocean management by Michael Onyema Edeh, Surjeet Dalal, Musaed Alhussein, Khursheed Aurangzeb, Bijeta Seth, Kuldeep Kumar

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Fungi-Kcr: a language model for predicting lysine crotonylation in pathogenic fungal proteins by Yong-Zi Chen, Yong-Zi Chen, Xiaofeng Wang, Zhuo-Zhi Wang, Haixin Li, Haixin Li

“…Moreover, our results indicate that a general predictive model performs better than species-specific models. …”
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A Model for Predicting IoT User Behavior Based on Bayesian Learning and Neural Networks by Xin Xu, Chengning Huang, Yuquan Zhu

“…To facilitate the allocation of energy and resources in the Internet of Things system, this paper presents a model for predicting user behavior in Internet of Things environments. …”
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A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin by Hugo J. M. Miniere, Ernesto A. B. F. Lima, Guillermo Lorenzo, David A. Hormuth II, Sophia Ty, Amy Brock, Thomas E. Yankeelov

“…We present a data assimilation-prediction pipeline with a two-phenotype model that includes a spatiotemporal component to characterize and predict the evolution of in-vitro breast cancer cells and their heterogeneous response to chemotherapy. …”
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Comparative Analysis of Machine Learning Models for Predicting Contaminant Concentration Distributions in Hospital Wards by Chonggang Zhou, Yunfei Ding

“…Four common machine learning models—multiple linear regression (MLR), support vector regression (SVR), backpropagation (BP) neural network, and convolutional neural network (CNN)—were employed to predict the distribution of contaminants within the wards. …”
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