AI-driven disinformation: policy recommendations for democratic resilience by Alexander Romanishyn, Olena Malytska, Vitaliy Goncharuk

“…This phenomenon poses a direct challenge to democratic processes, as algorithmically amplified falsehoods systematically distort political information environments, erode public trust in institutions, and foster polarization – conditions that degrade democratic decision-making. …”
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A machine learning-based approach to predict depression in Chinese older adults with subjective cognitive decline: a longitudinal study by Jing Xu, Wenjin Zhang, Wenli Liu

“…Depression was assessed with the CESD-10 scale. Three machine learning models—Gradient Boosting, Random Forest, and Boosted XGBoost—were used to predict depression risk over three years, incorporating 10 demographic, 5 health, 13 chronic disease, 3 lifestyle, and 2 physical function factors. …”
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Prognostic prediction for inflammatory breast cancer patients using random survival forest modeling by Yiwei Jia, Chaofan Li, Cong Feng, Shiyu Sun, Yifan Cai, Peizhuo Yao, Xinyu Wei, Zeyao Feng, Yanbin Liu, Wei Lv, Huizi Wu, Fei Wu, Lu Zhang, Shuqun Zhang, Xingcong Ma

“…Conclusion: In this study, we constructed a prognosis prediction model for IBC patients through RSF algorithm, which may potentially serve as a useful tool during clinical decision-making.…”
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Machine learning's model-agnostic interpretability on the prediction of students' academic performance in video-conference-assisted online learning during the covid-19 pandemic by Eka Miranda, Mediana Aryuni, Mia Ika Rahmawati, Siti Elda Hiererra, Albert Verasius Dian Sano

“…Result: The SMOTE improved the performance of three algorithms, with RF outperforming SVM and GNB in almost all tests, achieving an accuracy of 79.45%, precision of 75.71%, and recall of 79.45%. …”
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Predictive Modelling of nephrotoxicity from vancomycin and piperacillin-tazobactam (VPT) combination and vancomycin as monotherapy: an artificial intelligence (AI) Approach by Dr Winnie Lee, Mr William J Bolton, Mr Richard C Wilson, Professor Pantelis Georgiou, Professor Alison H Holmes, Dr Nina Zhu, Dr Timothy M Rawson

“…This aligns with our hypothesis that as vancomycin dosage escalates, the odds of AKI occurrence increase. Neural network and decision tree models will also be built to assess accuracy of prediction across these machine learning algorithms. …”
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Methodological Approaches to Assessing External Labor Migration Impact on the Financial and Budgetary Sphere of Host Countries by I. A. Aleshkovskii, A. A. Grebenyuk, A. S. Maksimova

“…The method lies in using a quantitative analysis algorithm consisting of three stages. The first stage is to identify specific positive and negative effects of labor immigration on the financial and budgetary sphere of the host country. …”
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ON THE EXPANSION OF THE WAREHOUSE BASE IN THE CONSIDERED ECONOMIC AREA WITH PARALLEL DETERMINATION OF THE OPTIMAL LOGISTICS WORK by R. Rogulin, V. Maksimenko, V. Zhandarmov, E. Pugacheva, V. Matveyev, D. Rogulin

“…This article proposes a comprehensive solution of three linear programming problems: Transport problem (logistics problem), Maximum flow problem, Center allocation problem. …”
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Evaluating Leaf Water Potential of Maize Through Multi-Cultivar Dehydration Experiments and Segmentation Thresholding by Shuanghui Zhao, Yanqun Zhang, Pancen Feng, Xinlong Hu, Yan Mo, Hao Li, Jiusheng Li

“…The analysis screened published VIs highly correlated with <i>Ψ_leaf</i> and constructed a model for <i>Ψ_leaf</i> estimation based on three algorithms—partial least squares regression (PLSR), random forest (RF), and multiple linear stepwise regression (MLR)—for each cultivar and all three cultivars. …”
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Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases by Huai-wen Zhang, Yi-ren Wang, Bo Hu, Bo Song, Zhong-jian Wen, Lei Su, Xiao-man Chen, Xi Wang, Ping Zhou, Xiao-ming Zhong, Hao-wen Pang, You-hua Wang

“…By using various machine-learning algorithms, including random forest, support vector machine, gradient boosting machine, XGBoost, decision tree, artificial neural network, k-nearest neighbors, LightGBM, and CatBoost algorithms, a stacking ensemble model was developed to classify gross tumor volume (GTV), brainstem, and normal brain tissue based on radiomic features. …”
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Assessing the Soldier Survivability Tradespace Using a Single IMU by Matthew P. Mavor, Victor C. H. Chan, Kristina M. Gruevski, Linda L. M. Bossi, Thomas Karakolis, Ryan B. Graham

“…Across all three approaches, we obtained an average accuracy of 90.0&#x0025;. …”
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Uncovering candidate Nanog-Helper genes in early mouse embryo differentiation using differential entropy and network inference by Francisco Prista von Bonhorst, Olivier Gandrillon, Ulysse Herbach, Corentin Robert, Claire Chazaud, Yannick De Decker, Didier Gonze, Geneviève Dupont

“…The results revealed that these three genes exhibit reciprocal activation with Nanog at the 32-cell stage. …”
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A Deep Learning Approach Based on Interpretable Feature Importance for Predicting Sports Results by Bendiaf Messaoud, Khelifi Hakima, Mohdeb Djamila, Belazzoug Mouhoub, Saifi Abdelhamid

“…As a multiclass classification problem with three classes, each match can have three possible outcomes. …”
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Multi-Objective Optimization of Urban Residential Envelope Structures in Cold Regions of China Based on Performance and Economic Efficiency by Kezheng Deng, Yanqiu Cui, Qingtan Deng, Ruixia Liu, Zhengshu Chen, Siyu Wang

“…Through field research and typological analysis of residential buildings in Jinan, a cold region of China, three construction eras were classified: Period I (1980–1985), Period II (1986–1995), and Period III (1996–2005). …”
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Optimization location routing problem (LRP) of humanitarian aid distribution in Sigi district using NSGA II methods by Serli Bombang, Bonivasius Prasetya Ichiarto, Humiras Hardi Purba

“…Optimization is designed into two scenarios, namely the construction of two distribution centers and three distribution centers. The result show that construction of two distribution centers can be designed at locations D3 and D4 with a total cost of IDR406 280 000 and a maximum service time of 12.002 hours, while the construction of three distribution centers can be done at locations DC1, DC4 and DC 7 or with a total cost of IDR605 363 000 and a maximum service time of 7.4253 hours.This research develops a new mathematical model that optimizes humanitarian aid distribution by balancing the setup cost of distribution centers and minimizing travel time. …”
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YED-Net: Yoga Exercise Dynamics Monitoring with YOLOv11-ECA-Enhanced Detection and DeepSORT Tracking by Youyu Zhou, Shu Dong, Hao Sheng, Wei Ke

“…Future work aims to integrate 3D pose estimation to develop a closed-loop biomechanical analysis system, thereby advancing sports science toward intelligent decision-making paradigms.…”
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Enhancing shear strength predictions of UHPC beams through hybrid machine learning approaches by Sanjog Chhetri Sapkota, Ajad Shrestha, Moinul Haq, Satish Paudel, Waiching Tang, Hesam Kamyab, Daniele Rocchio

“…This study proposes hybrid ML models that integrate three nature inspired metaheuristic algorithms—Giant Armadillo Optimization (GOA), Spotted Hyena Optimization (SHO) and Leopard seal optimization (LSA)- Extreme Gradient Boosting (XGB) to predict the shear strength of UHPC beams. …”
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Large Language Models and Artificial Neural Networks for Assessing 1-Year Mortality in Patients With Myocardial Infarction: Analysis From the Medical Information Mart for Intensive... by Boqun Shi, Liangguo Chen, Shuo Pang, Yue Wang, Shen Wang, Fadong Li, Wenxin Zhao, Pengrong Guo, Leli Zhang, Chu Fan, Yi Zou, Xiaofan Wu

“…The predictive performance of the 3 models was assessed and compared using the Harrell C-statistic (C-index), the area under the receiver operating characteristic curve (AUROC), calibration plots, Kaplan-Meier curves, and decision curve analysis. …”
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Deep Reinforcement Learning for Efficient Scheduling of Ground-based Astronomical Observations by Hai Cao, Shaoming Hu, Junju Du, Xu Chen, Shuqi Liu, Shuai Feng, Bo Zhang, Yuchen Jiang

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Machine learning-based risk prediction model for pertussis in children: a multicenter retrospective study by Juan Xie, Run-wei Ma, Yu-jing Feng, Yuan Qiao, Hong-yan Zhu, Xing-ping Tao, Wen-juan Chen, Cong-yun Liu, Tan Li, Kai Liu, Li-ming Cheng

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Using elastography-based multilayer perceptron model to evaluate renal fibrosis in chronic kidney disease by Ziman Chen, Tin Cheung Ying, Jiaxin Chen, Chaoqun Wu, Liujun Li, Hui Chen, Ting Xiao, Yongquan Huang, Xuehua Chen, Jun Jiang, Yingli Wang, Wuzhu Lu, Zhongzhen Su

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