Machine learning based prediction of geotechnical parameters affecting slope stability in open-pit iron ore mines in high precipitation zone by John Gladious, Partha Sarathi Paul, Manas Mukhopadhyay

“…Feature importance and sensitivity analyses were performed using SHAP (SHapley Additive exPlanations) to identify the most influential factors affecting slope stability predictions. …”
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Analysing learning behaviour: A data-driven approach to improve time management and active listening skills in students by Vinayak Hegde, Vishrutha M, Pallavi M. Shanthappa, Rekha Bhat, Nisha Raveendran, Roshin C

“…Methodologically, the study began with comprehensive data collection through a survey, data preprocessing tasks and feature selection, followed by training and evaluating predictive models using various ML algorithms. …”
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MIDAS: a technology-enabled hub-and-spoke system for the collection and dissemination of high-quality medical datasets in India by Dibyajyoti Maity, Rohit Satish, Raghu Dharmaraju, Vijay Chandru, Rajesh Sundaresan, Harpreet Singh, Debnath Pal

“…Over the years, many medical imaging datasets have been published globally, but existing datasets do not contain enough samples from the population of the Indian subcontinent, leading to subpar performance of developed AI models when deployed in India. …”
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In Vitro Antiviral Activity of the Fungal Metabolite 6-Pentyl-α-Pyrone Against Bovine Coronavirus: A Translational Study to SARS-CoV-2 by Violetta Iris Vasinioti, Amienwanlen Eugene Odigie, Maria Stella Lucente, Luca Del Sorbo, Cristiana Catella, Elisabetta Casalino, Maria Michela Salvatore, Alessia Staropoli, Francesco Vinale, Maria Tempesta, Filomena Fiorito, Anna Andolfi, Alessio Buonavoglia, Annamaria Pratelli, Paolo Capozza

“…Considering that BCoV and SARS-CoV-2 are both members of the <i>Betacoronavirus</i> genus and share several key features, BCoV represents a valuable reference model for human coronavirus research. …”
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DRR-YOLO: A Study of Small Target Multi-Modal Defect Detection for Multiple Types of Insulators Based on Large Convolution Kernel by Mingming Hu, Jun Liu, Junfu Liu

“…Firstly, a new module DRR is proposed based on Dilated Re-param Block (DRB) and Dilation-wise Residual (DWR), which is combined with the C2f module of the YOLOv8 model to enhance the model&#x2019;s detection effect for targets at different scales; Secondly, the Large Separable Kernel Attention SPPF (LSPPF) module is proposed to replace the SPPF in the original model, which enables the model to better preserve the feature information of the target while streamlining the structure; In addition, the advantages of MPDIoU and Inner-IoU are combined, and the loss function of the original model is replaced with Inner-MPDIoU. …”
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Construction Concrete Price Prediction Based on a Double-Branch Physics-Informed Neural Network by Kaier Shi, Ruiqing Han, Zhipeng Li, Pan Guo

“…To improve the prediction accuracy of the DB-PINN model, a feature analysis of the effect of the raw material price factors on the construction concrete price is conducted. …”
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Estimating the impact of interventions against COVID-19: From lockdown to vaccination. by James Thompson, Stephen Wattam

“…Our model is based on collation, with agents performing activities and moving between locations accordingly. …”
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Ensembling Classical Machine Learning and Deep Learning Approaches for Morbidity Identification From Clinical Notes by Vivek Kumar, Diego Reforgiato Recupero, Daniele Riboni, Rim Helaoui

“…Finally, we have also used ensemble learning techniques over a large number of combinations of classifiers to improve the single model performance. For our experiments, we used the n2c2 natural language processing research dataset, released by Harvard Medical School. …”
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High-precision lung cancer subtype diagnosis on imbalanced exosomal data via Exo-LCClassifier by Siyu Zhan, Siyu Zhan, Hao Yu, Shuang Liu, Ke Qin, Lu Guo

“…Background and objectiveGene expression analysis plays a critical role in lung cancer research, offering molecular feature-based diagnostic insights that are particularly effective in distinguishing lung cancer subtypes. …”
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Identification of Abnormal Electricity Consumption Behavior of Low-Voltage Users in New Power Systems Based on a Combined Method by Jiaolong Gou, Xudong Niu, Xi Chen, Shuxin Dong, Jing Xin

“…In the first stage, the GBDT algorithm leverages its robust feature learning and nonlinear classification capabilities to perform coarse-grained classification, extracting global patterns and categorical information. …”
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Facing depression: evaluating the efficacy of the EmpkinS-EKSpression reappraisal training augmented with facial expressions – protocol of a randomized controlled trial by Marie Keinert, Lena Schindler-Gmelch, Lydia Helene Rupp, Misha Sadeghi, Klara Capito, Malin Hager, Farnaz Rahimi, Robert Richer, Bernhard Egger, Bjoern M. Eskofier, Matthias Berking

“…., body movement perception) features of interventions. Therefore, we aim to evaluate the efficacy of a cognitive restructuring task augmented with the performance of anti-depressive facial expressions in individuals with and without depression. …”
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Artificial Intelligence for Detecting COVID-19 With the Aid of Human Cough, Breathing and Speech Signals: Scoping Review by Mouzzam Husain, Andrew Simpkin, Claire Gibbons, Tanya Talkar, Daniel Low, Paolo Bonato, Satrajit S. Ghosh, Thomas Quatieri, Derek T. O'Keeffe

“…More than half of the included studies reported area-under-the-curve performance of greater than 0.90 on symptomatic and negative datasets while one study achieved 100% sensitivity in predicting asymptomatic COVID-19 from cough-, breathing- or speech-based acoustic features. …”
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The Ongoing Epidemics of Seasonal Influenza A(H3N2) in Hangzhou, China, and Its Viral Genetic Diversity by Xueling Zheng, Feifei Cao, Yue Yu, Xinfen Yu, Yinyan Zhou, Shi Cheng, Xiaofeng Qiu, Lijiao Ao, Xuhui Yang, Zhou Sun, Jun Li

“…This study examined the genetic and evolutionary features of influenza A/H3N2 viruses in Hangzhou (2010–2022) by analyzing 28,651 influenza-like illness samples from two sentinel hospitals. …”
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Is regulatory science ready for artificial intelligence? by Thomas Hartung, Maurice Whelan, Weida Tong, Robert M. Califf

“…Abstract Trust is key in AI for regulatory science, but its definition is debated. If AI models use different features yet perform similarly, which should be trusted? …”
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Individualized functional brain mapping machine learning prediction of symptom-change resulting from selective kappa-opioid antagonism in an anhedonic sample from a Fast-Fail trial by Matthew D. Sacchet, Joseph L. Valenti, Poorvi Keshava, Shane W. Walsh, Moria J. Smoski, Andrew D. Krystal, Diego A. Pizzagalli

“…Methods: Nine ensemble models were estimated using cortical, subcortical, and combined cortical subcortical features from individualized functional topographies to predict changes in symptoms of overall psychopathology (anhedonia, depression, anxiety). …”
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Selective adsorption of CO2 in TAMOF-1 for the separation of CO2/CH4 gas mixtures by Santiago Capelo-Avilés, Mabel de Fez-Febré, Salvador R. G. Balestra, Juanjo Cabezas-Giménez, Raiana Tomazini de Oliveira, Irene I. Gallo Stampino, Anton Vidal-Ferran, Jesús González-Cobos, Vanesa Lillo, Oscar Fabelo, Eduardo C. Escudero-Adán, Larry R. Falvello, José B. Parra, Paolo Rumori, Gemma Turnes Palomino, Carlos Palomino Cabello, Stefano Giancola, Sofia Calero, José Ramón Galán-Mascarós

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Supervised machine learning algorithms for the classification of obesity levels using anthropometric indices derived from bioelectrical impedance analysis by Rodrigo Yáñez-Sepúlveda, Aldo Vásquez-Bonilla, Rodrigo Olivares, Pablo Olivares, Juan Pablo Zavala-Crichton, Claudio Hinojosa-Torres, Catalina Muñoz-Strale, Frano Giakoni-Ramírez, Josivaldo de Souza-Lima, Jacqueline Páez-Herrera, Jorge Olivares-Arancibia, Tomás Reyes-Amigo, Guillermo Cortés-Roco, Juan Hurtado-Almonacid, Eduardo Guzmán-Muñoz, Nicole Aguilera-Martínez, José Francisco López-Gil, Boryi A. Becerra-Patiño, Juan David Paucar-Uribe, Exal Garcia-Carrillo, Vicente Javier Clemente-Suárez

“…These models can enhance the effectiveness of obesity screening in clinical and community settings.…”
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DeepSeek-AI-enhanced virtual reality training for mass casualty management: Leveraging machine learning for personalized instructional optimization. by Zhe Li, Lei Shi, Mingyu Pei, Wan Chen, Yutao Tang, Guozheng Qiu, Xibin Xu, Liwen Lyu

“…Machine learning models were trained to predict performance outcomes, and feature importance was assessed using the Gini index. …”
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Artificial intelligence in vaccine research and development: an umbrella review by Rabie Adel El Arab, May Alkhunaizi, May Alkhunaizi, Yousef N. Alhashem, Alissar Al Khatib, Munirah Bubsheet, Salwa Hassanein, Salwa Hassanein

“…Nonetheless, persistent challenges emerged—data heterogeneity, algorithmic bias, limited regulatory frameworks, and ethical concerns over transparency and equity.Discussion and implicationsThese findings illustrate AI’s transformative potential across the vaccine lifecycle but underscore that translating promise into practice demands five targeted action areas: robust data governance and multi‑omics consortia to harmonize and share high‑quality datasets; comprehensive regulatory and ethical frameworks featuring transparent model explainability, standardized performance metrics, and interdisciplinary ethics committees for ongoing oversight; the adoption of adaptive trial designs and manufacturing simulations that enable real‑time safety monitoring and in silico process modeling; AI‑enhanced public engagement strategies—such as routinely audited chatbots, real‑time sentiment dashboards, and culturally tailored messaging—to mitigate vaccine hesitancy; and a concerted focus on global equity and pandemic preparedness through capacity building, digital infrastructure expansion, routine bias audits, and sustained funding in low‑resource settings.ConclusionThis umbrella review confirms AI’s pivotal role in accelerating vaccine development, enhancing efficacy and safety, and bolstering public acceptance. …”
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CXCR4/CXCL12 axis promotes lymphatic metastasis in tongue squamous cell carcinoma via PI3K/AKT signaling pathway by Huiquan Lou, Yichao Xia, Shengjie Shao, Xiang Liu, Zengzheng Li, Hongbin Yu, Yongsheng Li

“…An orthotopic TSCC mouse model was developed to validate findings in vivo. …”
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