Consumer Happiness in the Purchase of Electric Vehicles: a Fuzzy Logic Model by Fernando Lámbarry-Vilchis, Aboud Barsekh Onji, Leticia Refugio Chavarría López, Paola Judith Maldonado Colín

“…This research was conducted using a fuzzy Delphi method survey targeting a specific consumer group and two fuzzy inference systems: a multi-input single-output FIS model and an FIS Tree employing a hierarchical fuzzy inference structure, which leverages the survey's training data to optimize the models using different machine learning algorithms. The FIS tree model demonstrated superior efficacy in predicting the consumer satisfaction index, achieving an average forecast error of 0.65%. …”
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Removal mechanism and damage evolution of SiCp/Al composites based on FEM-MD model considering 3D random polyhedral particles in orthogonal cutting by Ming Li, Qingguang Li, Xianchao Pan, Jiaqi Wang, Zixuan Wang, Shengzhi Xu, Yunguang Zhou, Lianjie Ma, Tianbiao Yu

“…Experimental validation confirmed the multi-scale model's predictive accuracy for machining-induced surface damage. …”
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Fatigue Damage Prognosis Method for Main Girders of Cable-Stayed Bridges Based on Wavelet Neural Network by Shan Huang, Rui Chen, Jun Ling, Nan Jin

“…This method integrates WNN with multi-scale finite element modeling to predict fatigue damage progression. First, the theoretical foundation and implementation algorithms of the WNN are elaborated on and applied to forecast the future load environments of cable-stayed bridges. …”
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Improving Balanced Accuracy for Minority Plant Species under Data Imbalance by Ruben Gonzalez-Villanueva, Jose Carranza-Rojas

“…Regardless of the widely known success of deep learning in classification, such models are commonly measured by metrics that do not account for data imbalance, especially in terms of predictions per class, ignoring minority classes. This can be a problem, as minority classes are often the most difficult to predict and collect data for. …”
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Research of the state of the stress-realizing systems in pregnant women with miscarriage by V. A. Plotnik

“…The results of this work helps to develop algorithm for evaluation and prediction of the risk of miscarriage…”
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A prognostic glycolysis-related gene signature in osteosarcoma: implications for metabolic programming, immune microenvironment, and drug response by Naiqiang Zhu, Jingyi Hou, Yu Zhang, Ning Yang, KaiKai Ding, Chengbing Chang, Yanqi Liu, Haipeng Gu, Bin Chen, Xu Wei, Liguo Zhu

“…The prognostic efficacy of this risk signature was assessed via Kaplan–Meier curve analysis and Cox regression, evaluating its independence as a prognostic indicator. Additionally, the predictive potential of the risk model for drug response was evaluated using the “OncoPredict” package. …”
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Effectiveness of biomarker-guided duration of antibiotic treatment in children hospitalised with confirmed or suspected bacterial infection: the BATCH RCT by Cherry-Ann Waldron, Philip Pallmann, Simon Schoenbuchner, Debbie Harris, Lucy Brookes-Howell, Céu Mateus, Jolanta Bernatoniene, Katrina Cathie, Saul N Faust, Josie Henley, Lucy Hinds, Kerry Hood, Chao Huang, Sarah Jones, Sarah Kotecha, Sarah Milosevic, Helen Nabwera, Sanjay Patel, Stéphane Paulus, Colin VE Powell, Jenny Preston, Huasheng Xiang, Emma Thomas-Jones, Enitan D Carrol

“…In the presence of robust AMS programmes to reduce antibiotic use, a PCT-guided algorithm may offer little added value. Future trials must include an implementation framework to improve trial intervention fidelity, and repeated cycles of education and training to facilitate implementation of biomarker-guided algorithms into routine clinical care. …”
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Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…Classification tasks (85.2%) dominated AI applications, with neural networks, particularly multilayer perceptron and convolutional neural networks being the most frequently used algorithms. AI applications were analyzed across three domains: (1) diagnosis, where mobile deep neural networks, convolutional neural network ensemble models, and mixed-scale attention-based models have improved diagnostic accuracy and efficiency; (2) treatment, where machine learning models, such as deep autoencoders combined with functional magnetic resonance imaging, electroencephalography, and clinical data, have enhanced treatment outcome predictions; and (3) management, where AI has facilitated case identification, epidemiological research, health care burden assessment, and risk factor exploration for postherpetic neuralgia and other complications. …”
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Application of PSO-Optimized Twin Support Vector Machine in Medium and Long-Term Load Forecasting under the Background of New Normal Economy by Xiang He, Yan Chen, Kai Hu, Lin Wan

“…Moreover, this paper uses the algorithm to debug the filter and studies the accurate prediction of the fine model by the progressive spatial mapping algorithm and the processing of the data by the vector fitting algorithm. …”
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Modelling of River-Groundwater Interactions under Rainfall Events Based on a Modified Tank Model by Wen Nie, Yong-chang Liang, Lin Chen, Wei Shao

“…Parameter training of our tank model includes two algorithms: (i) the nonincremental learning algorithm-based model can predict the pore water pressure (PWP) in a slope and river under a 65 mm/hr rainfall event (coarse material) with Nash–Sutcliffe efficiency (NSE) = 0.427 and −0.909 and (ii) the incremental learning algorithm-based model can predict the PWP in a slope and river with NSE = 0.994 and 0.995. …”
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Challenges and inequalities in the management of financing the tasks of local government units: a critical analysis by Arkadiusz Ciach

“…As a result of underestimating the educational subsidy, are local government units forced to redirect their funds to finance educational tasks at the expense of other public activity areas? …”
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Potential applications of a low-cost gas sensor to monitor enteric methane emission from ruminant animals by Mulisa F. Dida, Milad Bagheri Shirvan, Toshikazu Kawaguchi, Sergio C. Garcia, Luciano A. Gonzalez

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Temporal scalability analysis of spectral remote sensing and Machine Learning-Based models for forest mapping in the tropical region of Nigeria by K. Pawłuszek-Filipiak, D. Włodarczyk, K. Stuchły, F.E. Ikuemonisan

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Beam Scanning with Ultra‐Low Sidelobes and In‐Band Ultra‐Low Scattering Characteristics Empowered by Single Space‐Time‐Coding Radiation‐Scattering Metasurface by Lixin Jiang, Yongfeng Li, Hao Yang, Mingbao Yan, Jinming Jiang, Yunwei Zhang, Zhe Qin, Wanwan Yang, Hongya Chen, Yongqiang Pang, Zhihao Guo, Lin Zheng, Jiafu Wang, Shaobo Qu

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Identification and evaluation of metabolic mRNAs and key miRNAs in colorectal cancer liver metastasis by Guanxuan Chen, Shiwen Wang, Meng Zhang, Wenna Shi, Ruoyu Wang, Wanqi Zhu

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Measures of state support for increasing labor productivity: synchronization of state goals, interests and business opportunities by R. V. Plyusov, N. A. Bogdanova, O. L. Mitryakova, V. A. Umnov

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Learning new surgical techniques in low and middle income countries, approval processes, and the impact of artificial intelligence by Long Cong Duy Tran, Long Cong Duy Tran, Helal Metwalli, Helal Metwalli, Dat Tien Le, Dat Tien Le, Samuel Amo-Afful, Samuel Amo-Afful, Mario Salib Todry Gerges, Mario Salib Todry Gerges, Hajer Hatim Hassan Ahmed, Hajer Hatim Hassan Ahmed, Dinh Thi Kim Quyen, Dinh Thi Kim Quyen, Abdelrahman Gamil Gad, Abdelrahman Gamil Gad, Phillip Tran, Nguyen Tien Huy, Nguyen Tien Huy, Nguyen Tien Huy

“…AI-powered tools, such as virtual reality (VR) simulations and tele-mentoring platforms, provide independent skill assessments and expand access to high-quality surgical education. However, implementing AI in LMICs faces some challenges, including inadequate resources, financial constraints and ethical issues related to data security and Equitable algorithms. …”
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The curvilinear associations between Life’s Crucial 9 and frailty: cross-sectional study of NHANES 2003 - 2023 by Bo Wang, Chunqi Jiang, Ning Wang, Yinuo Qu, Jun Wang, Guang Zhao, Xin Zhang, Xin Zhang

“…To identify inflection points, we applied recursive partitioning algorithms in conjunction with a two-stage linear regression model. …”
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LEVELS OF PATIENTS EXPOSURE AND A POTENTIAL FOR OPTIMIZATION OF THE PET DIAGNOSTICS IN THE RUSSIAN FEDERATION by L. A. Chipiga, I. A. Zvonova, D. V. Ryzhkova, M. A. Menkov, М. B. Dolgushin

“…Low dose computed tomography protocols, justification of diagnostic and multiphase computed tomography protocols, application of tube current modulation system and modern reconstruction algorithms, education and training of the staff in the field of radiation protection should be used for optimization of radiation protection of patient.…”
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Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015–2018 by Danhui Mao, Junfang Mu, Yajing Li, Lu He, Qianhui Chai, Xin Zhao, Xiaojun Ren, Hui Cheng

“…Among the machine learning algorithms, Logistic Regression exhibited the best performance, with an Accuracy of 0.954 and an AUC-ROC area of 0.998. …”
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