Mixed Time/Event-Triggered Model Predictive Tracking Control for Networked Mobile Robots by Huixin Liu, Yonghua Lai, Hongsong Lian, Guobin Wang, Dongsheng Zheng

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Evaluation of multiple machine learning models predicting the results of hybrid imaging in primary hyperparathyroidism by Anna Drynda, Jacek Podlewski, Karolina Kucharczyk, Grzegorz Sokołowski, Anna Sowa-Staszczak, Alicja Hubalewska-Dydejczyk, Małgorzata Trofimiuk- Müldner

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Correction: Time series models for prediction of leptospirosis in different climate zones in Sri Lanka. by PLOS ONE Staff

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Predicting the distribution of Ixodes ricinus in Europe: integrating microclimatic factors into ecological niche models by Arda Cem Kuyucu, Olcay Hekimoglu, Ala Tabor

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A hybrid LSTM-transformer model for accurate by Tianren Zhao, Yanhui Zhang, Minghao Wang, Wei Feng, Shengxian Cao, Gong Wang

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A Hybrid Network Analysis and Machine Learning Model for Enhanced Financial Distress Prediction by Saba Taheri Kadkhoda, Babak Amiri

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Dropout Prediction Model for College Students in MOOCs Based on Weighted Multi-feature and SVM by Zhang Yujiao, Ang Ling Weay, Shi Shaomin, Sellappan Palaniappan

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A model to predict outlet stores’ ratings using value, quality, selection, and help by Khalid M. Dubas, Saeed M. Dubas, David J. Hill

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Correction: Machine learning-based e-commerce platform repurchase customer prediction model. by Cheng-Ju Liu, Tien-Shou Huang, Ping-Tsan Ho, Jui-Chan Huang, Ching-Tang Hsieh

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The Prediction of Serum C-Reactive Protein Concentration Using Nonlinear Mixed-Effects Model by Suk Joo Bae, Gyu Ri Kim, Sun Geu Chae, Yeesuk Kim

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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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Wind Power Prediction Based on a Hybrid Model of ICEEMDAN and ModernTCN-Informer by Jun He, Zijian Cheng, Zijie Zhong, Lizhuo Liang, Jianhui Ye

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Bayesian compositional generalized linear mixed models for disease prediction using microbiome data by Li Zhang, Xinyan Zhang, Justin M. Leach, A. K. M. F. Rahman, Carrie R. Howell, Nengjun Yi

“…Abstract The primary goal of predictive modeling for compositional microbiome data is to better understand and predict disease susceptibility based on the relative abundance of microbial species. …”
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DNN-based Software Reliability Model for Fault Prediction and Optimal Release Time Determination by Shikha Dwivedi, Neeraj Kumar Goyal, Hariom Chaudhari

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Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist. by Karel G M Moons, Joris A H de Groot, Walter Bouwmeester, Yvonne Vergouwe, Susan Mallett, Douglas G Altman, Johannes B Reitsma, Gary S Collins

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Real-time prediction system for prevention of acute renal failure based on AI model by Shih-Chang Hsia, Szu-Hong Wang, Liang-Fu Chen, Bo-An Ko

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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

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Anemia Risk Prediction Model for Osteosarcoma Patients Post‐Chemotherapy Using Artificial Intelligence by Zhiping Su, Zhiwei Nong, Feihong Huang, Chengxing Zhou, Chaojie Yu

“…A web model application was created (https://anemic‐prediction‐of‐osteosarcoma.shinyapps.io/DynNomapp/). …”
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GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity by Junwei Luo, Ziguang Zhu, Zhenhan Xu, Chuanle Xiao, Jingjing Wei, Jiquan Shen

“…Finally, the obtained drug and protein feature vectors are combined to predict DTA through the fully connected layer. The source code can be downloaded from https://github.com/zhuziguang/GS-DTA . …”
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Predictive models for the surface roughness and subsurface damage depth of semiconductor materials in precision grinding by Shang Gao, Haoxiang Wang, Han Huang, Zhigang Dong, Renke Kang

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