Predictive Factors for Fetal Growth Restriction in Patients with Preeclampsia: A Clinical Prediction Study by Yan M, Li F, Jun S, Li L, You W, Hu L

Subjects: “…preeclampsia fetal growth restriction predictive model nomogram risk factors…”
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Data Mining Techniques for Predictive Maintenance in Manufacturing Industries a Comprehensive Review by Chinthamu Narender, Ashish, P Mathiyalagan, B Devananda Rao, S Kannadhasan, M Suganya

Subjects: “…predictive maintenance (pdm)…”
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An improved model-free predictive voltage control for grid-forming inverter with adaptive ultra-local data-model in renewable energy system by Yifu Lin, Junwei Zhu, Feng He

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Leveraging Historical Process Data for Recombinant <i>P. pastoris</i> Fermentation Hybrid Deep Modeling and Model Predictive Control Development by Emils Bolmanis, Vytautas Galvanauskas, Oskars Grigs, Juris Vanags, Andris Kazaks

“…Hybrid modeling techniques are increasingly important for improving predictive accuracy and control in biomanufacturing, particularly in data-limited conditions. …”
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Enhanced and predictive modelling of direct shoot regeneration of Evolvulus alsinoides (L.) using ANN machine learning model and genetic stability studies by Collince Omondi Awere, Kasinathan Rakkammal, Andaç Batur Çolak, Mustafa Bayrak, Ogolla Fredrick, Valentine Chikaodili Anadebe, Manikandan Ramesh

“…The model may be used as a dependable and accurate predictive technique for ensuing investigations in in vitro plant genetic engineering.…”
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Integration of deep learning and railway big data for environmental risk prediction models and analysis of their limitations by Liuhui Quan, Minjie Wang, Lyu Baihang, Zhang Ziwen, Zhang Ziwen, Zhang Ziwen

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Smart Microgrid Management and Optimization: A Systematic Review Towards the Proposal of Smart Management Models by Paul Arévalo, Dario Benavides, Danny Ochoa-Correa, Alberto Ríos, David Torres, Carlos W. Villanueva-Machado

“…Future research should address the standardization of communication protocols, development of explainable AI models, and creation of sustainable business models to enhance resilience, efficiency, and scalability. …”
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Using Hybrid Neural Networks to Improve Traffic Prediction and Congestion Management by Ali Abd Samir

Subjects: “…Traffic Prediction, Deep Learning, Graph-Based Models, DCRNN, METR-LA, Congestion Management…”
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Multi-Sensor Heterogeneous Signal Fusion Transformer for Tool Wear Prediction by Ju Zhou, Xinyu Liu, Qianghua Liao, Tao Wang, Lin Wang, Pin Yang

Subjects: “…tool wear prediction…”
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Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins by Senlin Tang, Fubao Sun, Wenbin Liu, Hong Wang, Yao Feng, Ziwei Li

“…Abstract Streamflow prediction in ungauged basins (PUB) is challenging, and Long Short‐Term Memory (LSTM) is widely used to for such predictions, owing to its excellent migration performance. …”
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In Silico tool for predicting, designing and scanning IL-2 inducing peptides by Naman Kumar Mehta, Anjali Lathwal, Rajesh Kumar, Dilraj Kaur, Gajendra P. S. Raghava

“…Subsequently, we developed artificial intelligence-based models, including machine learning (ML), deep learning (DL), and large language models (LLM), to predict IL-2-inducing peptides. …”
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A Digital Shadow for Modeling, Studying and Preventing Urban Crime by Juan Palma-Borda, Eduardo Guzman, Maria-Victoria Belmonte

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Predict the carcinogenicity of compounds with SGCN by Wei Ruobing, He Jiafeng, Qiu Xiaofang, Liu Qi

“…The results showed that when compared to other models, the classification model of the SGCN was more suited to predicting the carcinogenicity of compounds and had an overall classification accuracy of 96.9%, which showed that the SGCN model could accurately classify chemicals and had considerable potential in practical applications.…”
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Comparative Analysis of Machine Learning Models for Predicting Interfacial Bond Strength of Fiber-Reinforced Polymer-Concrete by Miljan Kovačević, Marijana Hadzima-Nyarko, Predrag Petronijević, Tatijana Vasiljević, Miroslav Radomirović

“…The evaluation was based on their predictive accuracy. The optimal model identified was the GPR ARD Exponential model, which achieved a mean absolute error (MAE) of 1.8953 MPa and a correlation coefficient (R) of 0.9658. …”
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Unveiling postpartum PTSD: predicting risk factors using decision trees and logistic regression in Chinese women by Xiao Fei Nie, Lan Lan Xu, Wen Ping Guo, Jin Hui Li, Li Cheng, Tao Tao Zhang, Jun-Yan Li

“…This study aims to explore the factors associated with postpartum posttraumatic stress disorder (PP-PTSD) in Chinese women using decision tree and logistic regression models, while also comparing the predictive performance of both approaches. …”
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A fair and efficient two-step procedure for sugarcane properties prediction based on near-infrared spectra by Luiz Alexandre Peternelli, Andréa Carla Bastos Andrade, Cristina Silva Dias, Reinaldo Francisco Teófilo

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An artificial intelligence model to predict mortality among hemodialysis patients: A retrospective validated cohort study by Zhong Peng, Shuzhu Zhong, Xinyun Li, Fengyi Yu, Zixu Tang, Chunyuan Ma, Zihao Liao, Song Zhao, Yuan Xia, Haojun Fu, Wei Long, Mingxing Lei, Zhangxiu He

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The challenges for developing prognostic prediction models for acute kidney injury in hospitalized children: A systematic review by Chen Wang, Xiaohang Liu, Chao Zhang, Ruohua Yan, Yuchuan Li, Xiaoxia Peng

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Comparison of exposure assessment models, expert judgment and Bayes analysis, in Prediction of the tile industry respiratory exposures by MJ Zare Sakhvidi, H Mihanpoor, H Falahzadeh, M Mostaghaci, GH Halvani, F Samouri

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Predictive density profile control with discrete pellets, applied to integrated simulations of ITER by C.A. Orrico, M. van Berkel, T.O.S.J. Bosman, L. Ceelen, W.P.M.H. Heemels, F. Koechl, D. Krishnamoorthy

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