Fractional Uncertain Forecasting of the Impact of Groundwater Over-Exploitation on Temperature in the Largest Groundwater Depression Cone by Xiangyue Ren, Liyuan Ren, Lifeng Wu

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Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

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Data-driven hybrid SARIMAX-MLP framework for energy consumption prediction in residential micro-grid by Ibrahim Ali Kachalla, Christian Ghiaus, Adeniran Ademuwagun, Olufemi Babajide Odeyinde, Majid Baseer

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Relevance vector machine and multivariate adaptive regression spline for modelling ultimate capacity of pile foundation by Pijush Samui, Mohamed A. Shahin

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A Brief Overview of Modeling Estimation of State of Health for an Electric Vehicle’s Li-Ion Batteries by Ehab H. E. Bayoumi, Michele De Santis, Hilmy Awad

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Prediction of the Ecological Behavior of <i>Burkholderia gladiolus</i> in Fresh Wet Rice Noodles at Different Temperatures and Its Correlation with Quality Changes by Mengmeng Li, Ke Xiong, Wen Jin, Yumeng Hu

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Evaluation of the impact of COVID-19 pandemic on hospital admission related to common infections: Risk prediction models to tackle antimicrobial resistance in primary care. by Ali Fahmi, Victoria Palin, Xiaomin Zhong, Ya-Ting Yang, Simon Watts, Darren M Ashcroft, Ben Goldacre, Brian MacKenna, Louis Fisher, Jon Massey, Amir Mehrkar, Seb Bacon, OpenSAFELY Collaborative, Kieran Hand, Tjeerd Pieter van Staa

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Hindcasting Extreme Significant Wave Heights Under Fetch-Limited Conditions with Tree-Based Models by Damjan Bujak, Hanna Miličević, Goran Lončar, Dalibor Carević

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Development and validation of a nomogram to predict failure of initial radioactive iodine therapy in differentiated thyroid cancer: a retrospective cohort study by Yulong Tang, Peng Wu, Shiwei Zhou, Hui Li, Xiaohua Song, Wu Li, Xiaowei Peng

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Comparison of methodologies for flow prediction through teleconnection indices. Case study: Paute river basin by Maria Daniela Gonzalez, Dario Xavier Zhina, Alexandra Guanuchi-Quito, Alex Aviles-Anazco

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Enhancing Particulate Matter Estimation in Livestock-Farming Areas with a Spatiotemporal Deep Learning Model by Dohyeong Kim, Heeseok Kim, Minseon Hwang, Yongchan Lee, Choongki Min, Sungwon Yoon, Sungchul Seo

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Enhancing the confidence of potential targets enriched by similarity-centric models: the crucial role of the similarity threshold by Ling-Fei Tong, You-Jin Ge, Su-Qing Yang

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Predicting the potential distribution change of the endangered Francois' langur (Trachypithecus francoisi) across its entire range in China under climate change by Yaqiong Wan, Luanxin Li, Jiang Zhou, Yue Ma, Yanjing Zhang, Yan Liu, Jiaqi Li, Wei Liu

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Integrating multi‐omics features enables non‐invasive early diagnosis and treatment response prediction of diffuse large B‐cell lymphoma by Weilong Zhang, Bangquan Ye, Yang Song, Ping Yang, Wenzhe Si, Hairong Jing, Fan Yang, Dan Yuan, Zhihong Wu, Jiahao Lyu, Kang Peng, Xu Zhang, Lingli Wang, Yan Li, Yan Liu, Chaoling Wu, Xiaoyu Hao, Yuqi Zhang, Wenxin Qi, Jing Wang, Fei Dong, Zijian Zhao, Hongmei Jing, Yanzhao Li

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Research progress on the application of machine learning in inflammatory skin diseases by GUO Jingxue, LIU Yongsheng, YANG Xueying, LI Jiaojiao, LI Dan, LI Yiqun, LI Yanfei, ZHANG Junjing

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Development and validation of an improved prediction model for vaginal birth after previous cesarean section: a retrospective cohort study of a Chinese population by Haiyan Liu, Yi Yu, Xiaoyue Zhang, Jiangnan Pei, Yao Tang, Rong Hu, Weirong Gu

“…Internal validation performed by bootstrap resampling, calibration curves, and Hosmer-Lemeshow test confirmed the model’s robust performance. An optimal predicted probability cut-off of 0.7 was identified by decision curve analysis and clinical considerations.Conclusions The improved predictive VBAC model exhibited adequate performance such that women with a prior low transverse cesarean delivery who scored 0.7 or higher (in the model-derived probability score) would consider TOLAC, potentially leading to a reduction in maternal-neonatal morbidity.Registration The study was approved by the Ethical Committee of Obstetrics and Gynecology Hospital, Fudan University (2018-43) and was registered in the Chinese Clinical Trial Registry (ChiCTR1900022484), https://www.chictr.org.cn/showproj.html?…”
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Abnormal resting-state effective connectivity of triple network predicts smoking motivations among males by Mengzhe Zhang, Jieping Sun, Qiuying Tao, Jinghan Dang, Weijian Wang, Shaoqiang Han, Yarui Wei, Jingliang Cheng, Yong Zhang

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LinU-Mamba: Visual Mamba U-Net with Linear Attention to Predict Wildfire Spread by Henintsoa S. Andrianarivony, Moulay A. Akhloufi

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Prediction of Current and Future Distributions of Chalcophora detrita (Coleoptera: Buprestidae) Under Climate Change Scenarios by Arif Duyar, Muhammed Arif Demir, Mahmut Kabalak

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Synthetic fibrosis distributions for data augmentation in predicting atrial fibrillation ablation outcomes: an in silico study by Alexander M. Zolotarev, Alexander M. Zolotarev, Kiane Johnson, Kiane Johnson, Yusuf Mohammad, Omnia Alwazzan, Omnia Alwazzan, Gregory Slabaugh, Gregory Slabaugh, Caroline H. Roney, Caroline H. Roney

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