What factors influence the willingness and intensity of regular mobile physical activity?— A machine learning analysis based on a sample of 290 cities in China by Hao Shen, Bo Shu, Jian Zhang, Yaoqian Liu, Ali Li

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Development of machine learning models for predicting non-remission in early RA highlights the robust predictive importance of the RAID score-evidence from the ARCTIC study by Gaoyang Li, Shrikant S. Kolan, Franco Grimolizzi, Joseph Sexton, Giulia Malachin, Guro Goll, Tore K. Kvien, Tore K. Kvien, Nina Paulshus Sundlisæter, Manuela Zucknick, Siri Lillegraven, Espen A. Haavardsholm, Espen A. Haavardsholm, Bjørn Steen Skålhegg

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Identification of EGR1 as a Key Diagnostic Biomarker in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) Through Machine Learning and Immune Analysis by Wu X, Pan T, Fang Z, Hui T, Yu X, Liu C, Guo Z, Liu C

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Quantifying the Carbon Reduction Potential of Urban Parks Under Extreme Heat Events Using Interpretable Machine Learning: A Case Study of Jinan, China by Lemin Yu, Wenru Li, Changhui Zheng, Xiaowen Lin

“…This study systematically evaluated the carbon reduction potential of 369 urban parks in Jinan during extreme heat events using land surface temperature (LST) retrieval, combined with CatBoost + SHAP machine learning methods. Results indicate that the LST in Jinan ranged from 1.77 °C to 59.44 °C, and 278 parks exhibited significant cooling effects, collectively saving 2943 tons of CO₂ per day—offsetting 11.28% of the city’s fossil fuel emissions. …”
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Temperature Is a Key Factor Affecting Total Phosphorus and Total Nitrogen Concentrations in Northeastern Lakes Based on Sentinel-2 Images and Machine Learning Methods by Haoming Qin, Chong Fang, Ge Liu, Kaishan Song, Zhuoshi Li, Sijia Li, Hui Tao, Zhaojiang Yan

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Deciphering the role of metal ion transport-related genes in T2D pathogenesis and immune cell infiltration via scRNA-seq and machine learning by Zuhui Pu, Zuhui Pu, Tony Bowei Wang, Ying Lu, Ying Lu, Zijing Wu, Zijing Wu, Yuxian Chen, Ziqi Luo, Xinyu Wang, Lisha Mou, Lisha Mou

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Retraction Note: Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients by Xiliang Zhang, Hanjie Guo, Xiaolong Li, Wei Tao, Xiaoqing Ma, Yuxing Zhang, Weidong Xiao

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Innovación en sueño by Laura Vigil, Toni Zapata, Andrea Grau, Marta Bonet, Montserrat Montaña, María Piñar

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Neural network potentials for exploring condensed phase chemical reactivity by Gomez, Axel, de la Puente, Miguel, David, Rolf, Laage, Damien

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Applications of Artificial Intelligence for Precision Agriculture by Yiannis Ampatzidis

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A Data-Driven Methodology for Obtaining the Stress–Strain Curves of Metallic Materials Using Discrete Indentation Tests by Nitzan Rom, Elad Priel

Subjects: “…machine learning…”
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Automating Historical Source Transcription by Gunnar Thorvaldsen

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Using Convolutional Neural Networks for segmentation of brain tumors by Kauã Gabriel Silva de Lima, Vagner Alves Ferreira da Silva, João Victor Oliveira da Silva, Lucas Patrick Ramos de Oliveira, Diogo Lopes da Silva

Subjects: “…Machine Learning…”
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Seismic Prediction of Porosity in the Norne Field: Utilizing Support Vector Regression and Empirical Models Driven by Bayesian Linearized Inversion by Jorge A. Teruya Monroe, Jose J. S. de Figueiredo, Carlos E. S. Amanajas

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Zero-shot Learning for Subdiscrimination in Pre-trained Models by Francisco Dominguez-Mateos, Vincent O’Brien, James Garland, Ryan Furlong, Daniel Palacios-Alonso

Subjects: “…Machine learning…”
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Applications of Artificial Intelligence for Precision Agriculture by Yiannis Ampatzidis

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A dataset of blood slide images for AI-based diagnosis of malariaDataverse by Rose Nakasi, Joyce Nakatumba Nabende, Jeremy Francis Tusubira, Aloyzius Lubowa Bamundaga, Alfred Andama

Subjects: “…Machine learning…”
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Deep-Learning-Driven Insights into Nitrogen Leaching for Sustainable Land Use and Agricultural Practices by Caixia Hu, Jie Li, Yaxu Pang, Lan Luo, Fang Liu, Wenhao Wu, Yan Xu, Houyu Li, Bingcang Tan, Guilong Zhang

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Development and validation of a deep learning system for detection of small bowel pathologies in capsule endoscopy: a pilot study in a Singapore institution by Bochao Jiang, Michael Dorosan, Justin Wen Hao Leong, Marcus Eng Hock Ong, Sean Shao Wei Lam, Tiing Leong Ang

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Rating pome fruit quality traits using deep learning and image processing by Nhan H. Nguyen, Joseph Michaud, Rene Mogollon, Huiting Zhang, Heidi Hargarten, Rachel Leisso, Carolina A. Torres, Loren Honaas, Stephen Ficklin

Subjects: “…machine learning…”
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