A Machine Learning-Based Computational Methodology for Predicting Acute Respiratory Infections Using Social Media Data by Jose Manuel Ramos-Varela, Juan C. Cuevas-Tello, Daniel E. Noyola

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TCB: A feature transformation method based central behavior for user interest prediction on mobile big data by Chen Zhou, Hao Jiang, Yanqiu Chen, Jing Wu, Jianguo Zhou, Yuanshan Wu

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A Deep Learning Algorithm for Multi-Source Data Fusion to Predict Effluent Quality of Wastewater Treatment Plant by Shitao Zhang, Jiafei Cao, Yang Gao, Fangfang Sun, Yong Yang

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Prediction of thermal conductivity of 93W–Ni–Fe alloys in sintering process based on finite element analysis by YIN Gang, PAN Qian, ZHAO Teng, YIN Haiqing, WANG Yongwei, QU Xuanhui, XIONG Ning

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Research on Multi-Step Prediction of Pipeline Corrosion Rate Based on Adaptive MTGNN Spatio-Temporal Correlation Analysis by Mingyang Sun, Shiwei Qin

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Multimodal Representation Learning Based on Personalized Graph-Based Fusion for Mortality Prediction Using Electronic Medical Records by Abdulrahman Al-Dailami, Hulin Kuang, Jianxin Wang

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Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

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Histogram-based gradient boosting machine with SHAP-driven interpretability for predicting intensity of urban heat Island effect by Nhat-Duc Hoang

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State of Health Prediction for Lithium-Ion Batteries Based on Gated Temporal Network Assisted by Improved Grasshopper Optimization by Xiankun Wei, Silun Peng, Mingli Mo

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Prediction and Analysis of Transient Electric Field in DC Yard of Flexible Converter Station Under Short-Circuit Conditions by Sihang WU, Hong SHEN, Lei QI, Peng QIU, Zhaoxia KUAI

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Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning. by Steven Cogill, Shriram Nallamshetty, Natalie Fullenkamp, Kent Heberer, Julie Lynch, Kyung Min Lee, Mihaela Aslan, Mei-Chiung Shih, Jennifer S Lee

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Prospects for the Integration of Google Trends Data and Official statistics to Assess social Comfort and Predict the Financial situation of the Population by M. V. Shakleinaa, M. I. Volkova, K. I. Shaklein, S. R. Yakiro

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CerviXpert: A multi-structural convolutional neural network for predicting cervix type and cervical cell abnormalities by Rashik Shahriar Akash, Radiful Islam, SM Saiful Islam Badhon, KSM Tozammel Hossain

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Predicting outcomes after moderate and severe traumatic brain injury using artificial intelligence: a systematic review by Armaan K. Malhotra, Husain Shakil, Christopher W. Smith, Yu Qing Huang, Jethro C. C. Kwong, Kevin E. Thorpe, Christopher D. Witiw, Abhaya V. Kulkarni, Jefferson R. Wilson, Avery B. Nathens

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Soil Moisture Prediction Using Remote Sensing and Machine Learning Algorithms: A Review on Progress, Challenges, and Opportunities by Manoj Lamichhane, Sushant Mehan, Kyle R. Mankin

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A traffic prediction method for missing data scenarios: graph convolutional recurrent ordinary differential equation network by Ming Jiang, Zhiwei Liu, Yan Xu

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Spatiotemporal prediction of soil organic carbon density in Europe (2000–2022) using earth observation and machine learning by Xuemeng Tian, Sytze de Bruin, Rolf Simoes, Mustafa Serkan Isik, Robert Minarik, Yu-Feng Ho, Murat Şahin, Martin Herold, Davide Consoli, Tomislav Hengl

“…Prediction accuracy varies by land cover, depth interval and year of prediction with the worst accuracy for shrubland and deeper soils 100–200 cm. …”
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Enhancing laparoscopic surgery training: a comparative study of traditional models and automated error detection system by Yitian Luo, Jingjie Wang, Zongting Yan, Jingjing He, Liye Fu, Shenghan Wang, Ying Han, Yaoyu Fu, Xiandi Wang, Kang Li, Rong Yin, Dan Pu

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MD-Syn: synergistic drug combination prediction based on a multidimensional feature fusion method and attention mechanisms by XinXin Ge, Yi-Ting Lee, Shan-Ju Yeh, Shan-Ju Yeh, Shan-Ju Yeh

“…To facilitate broader community access to this model, we have developed a web portal (https://labyeh104-2.life.nthu.edu.tw/) that enables customized predictions of drug combination synergy effects based on user-specified compounds.…”
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Predictions for the Detectability of Milky Way Satellite Galaxies and Outer-Halo Star Clusters with the Vera C. Rubin Observatory by Kabelo Tsiane, Sidney Mau, Alex Drlica-Wagner, Jeffrey L. Carlin, Peter S. Ferguson, Keith Bechtol, Ethan O. Nadler, Annika H. G. Peter, Yao-Yuan Mao, Adam J. Thornton, LSST Dark Energy Science Collaboration

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