Economic approach for optimal allocation of irrigation water in water-scarce region by Xueliang Zhang, Li Ren, Jianshi Zhao

“…Optimizing irrigation water allocation is critical for maximizing grain yields in water-scarce regions. Traditional algorithms face challenges such as lack of interpretable criteria, the curse of dimensionality, and instability. …”
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The application of statistical methods to assess economic assets by D. V. Dianov

“…The application of mathematical-statistical apparatus, therefore, is an objective necessity for obtaining general indicators of the size of the national wealth.In conclusion, we can mention about the methodical approaches, the building of model algorithms application of statistical methods in solving scientific and practical problems, depending on the identification belonging of the valued objects. …”
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Antiviral therapy can effectively suppress irAEs in HBV positive hepatocellular carcinoma treated with ICIs: validation based on multi machine learning by Shuxian Pan, Zibing Wang

“…Predictive models were constructed using three machine learning algorithms to analyze and statistically evaluate clinical characteristics, including immune cell data. …”
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A Novel Tool for Biodiversity Studies: Earthworm Classification via NGS and Neural Networks by Tadeusz Malewski, Ewa Ropelewska, Andrzej Skwiercz, Anastasiia Lutsiuk, Anita Zapałowska

“…Textures after selection were used to develop classification models using machine learning algorithms. The earthworms <i>Eisenia fetida</i>, <i>Dendrobaena</i> ssp., and <i>Lumbricus terrestris</i> were distinguished with the accuracy reaching 100% for models built using Logistic, Ensemble, and Narrow Neural Network. …”
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Data-driven EV charging infrastructure with uncertainty based on a spatial–temporal flow-driven (STFD) models considering batteries by Talal Alharbi, Ahmed Abdalrahman, Mostafa H. Mostafa

“…The developed mathematical frameworks and algorithms facilitate the optimal sizing and siting of both EV charging stations and ESS. …”
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Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…The National Health and Nutrition Examination Survey (NHANES) 2012–2018 data comprising audiometric tests and cardiovascular risk factors was utilized. Machine learning algorithms were trained to classify hearing impairment thresholds and predict pure tone average values. …”
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Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization by Waqar Ashiq, Samra Kanwal, Adnan Rafique, Muhammad Waqas, Tahir Khurshaid, Elizabeth Caro Montero, Alicia Bustamante Alonso, Imran Ashraf

“…The novel hybrid model integrates deep learning (DL) and transformer models for automatic feature extraction, combined with machine learning algorithms (MLAs) for classification. To further enhance model performance, we employ several hyperparameter optimization (HPO) techniques, including Grid Search (GS), Randomized Search (RS), and Bayesian Optimization with Gaussian Processes (BOGP). …”
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Predicting mortality risk in Alzheimer’s disease using machine learning based on lifestyle and physical activity by Ruihong Tang, Liang Tan, Xia Chen, Zhengwu Shan, Zhao Zhang, Panpan Cheng

“…Lifestyle and physical activity levels were identified as significant predictors influencing mortality risk. ML algorithms, notably RSF, effectively predict mortality risk in AD patients, demonstrating clear advantages over traditional statistical models. …”
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Evaluation of Modified Reflection Symmetry Decomposition Polarization Features for Sea Ice Classification by Tianlang Lan, Chengfei Jiang, Xiaofan Luo, Wentao An

“…Three machine learning algorithms, Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machines (SVM), were also used for the comparative analysis. …”
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Higher-order aberrations and spherical aberration in various age groups after LASIK and cataract surgery by Robert Edward T. Ang, Patricia L. Lee, Ryan S. Torres, Michelle Marie Q. Araneta, Emerson M. Cruz, Maria Socorro M. Torno

“…Treated patients were classified into 2 groups according to treatment administered: eyes that underwent different algorithms of laser in situ keratomileusis (Lasik) demonstrating quantifiable differences in corneal aberrations, and eyes that underwent uncomplicated phacoemulsification with in-the-bag implantation of aspheric neutral EnVista MX60 (Bausch & Lomb, USA), negative aspheric Tecnis ZCB00 (Johnson and Johnson, USA), or spherical Akreos Adapt (Bausch & Lomb, USA) intraocular lens (IOL) showing differences in internal spherical aberrations. …”
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Development and validation of a nomogram for predicting low Kt/Vurea in peritoneal dialysis patients by Danfeng Zhang, Tian Zhao, Liting Gao, Huan Zhu, Haowei Jin, Guiling Liu, Deguang Wang

“…Univariate logistic regression, LASSO analysis, and Random Forest (RF) algorithms were employed to identify potential biomarkers. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…IMESc permits the customization of plots and saving the workflows into “savepoints” guarantying reproducibility. iMESc bridges the gap between the complexity of machine learning algorithms and the need for user-friendly interfaces in environmental research. …”
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Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis by Shanshan Wan, Shiping Wang, Xinyu He, Chao Song, Jiaping Wang

“…Therefore, challenges still exist in the current radiomics approaches for diagnosing RF, and further exploration of optimized artificial intelligence (AI) algorithms and technologies is needed.…”
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AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration by Tiffany I Leung, Andrew J Coristine, Arriel Benis

“…Further, there are concerns about ethical and legal issues, algorithmic bias, the potential for long-term “cognitive debt” from overreliance on AI, and even the potential loss of physician autonomy. …”
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Influence of Leadership on Human–Artificial Intelligence Collaboration by Rodrigo Zárate-Torres, C. Fabiola Rey-Sarmiento, Julio César Acosta-Prado, Nelson Alfonso Gómez-Cruz, Dorys Yaneth Rodríguez Castro, José Camargo

“…The thematic analysis allowed the identification of conceptual patterns and research gaps; the model elaborated from the review shows that leadership has an ethical and strategic mediation in the HI-AI relationship in a hybrid space of cooperation, in which automated decisions are put in real context through human judgment and reasoning; ethical governance mechanisms emerge for systems supported by artificial intelligence; and finally, a balancing mechanism to algorithmic efficiency is established through cognitive adaptability. …”
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A manganese metabolism-related gene signature stratifies prognosis and immunotherapy efficacy in kidney cancer by Yang Liu, Hao Ye, Ruoxuan Zhang, Xiaolong Liu, Ranlu Liu

“…Through integrated bioinformatics approaches, including differential expression analysis, univariate Cox regression, and three machine learning algorithms (Boruta, GBM, and RFS), we identified prognosis-related MMCG. …”
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Stacking ensemble learning models diagnose pulmonary infections using host transcriptome data from metatranscriptomics by Tian Zhang, Ying Deng, Wentao Wang, Zhe Zhao, Yiling Wu, Haoqian Wang, Shutao Xia, Weifang Liao, Weijie Liao

“…Leveraging these characteristic genes, we constructed classification sub-models employing 13 types of machine learning algorithms, and we further integrated these sub-models into stacking-based ensemble models with Lasso regression, resulting in diagnostic models that required only a small set of gene expression inputs. …”
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Exploring the key ingredients and mechanisms of Banxia Xiexin decoction for the treatment of polycystic ovary syndrome based on network pharmacology and experimental validation by Bai Hai, Yingying Zhang, Jing Huang, Richard Mprah, Mingming Wang

“…KEGG analysis showed they were mainly involved in signaling pathways such as PI3K-AKT, MAPK, HIF-1 and IL17. By PPI and algorithmic analysis, we identified 8 hub genes, 5 of which (JUN, MAPK1, MAPK3, FOS, TP53) were related to oxidative stress. …”
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Automatic generation of control solution for resource allocation using Petri net model Geração automática da solução de controle para alocação de recursos utilizando redes de Petri... by Francisco Yastami Nakamoto, Paulo Eigi Miyagi, Diolino José dos Santos Filho

“…The goal of this work is to introduce an algorithmic approach, which allows the implementation of a computer program based on FMS functional specification. …”
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Enhancing Healthcare With WBAN and Digital Twins: A Machine Learning Approach for Predictive Health Monitoring by Rishit Mahapatra, Deepak Sethi, Kaushik Mishra

“…These parameters feed into the digital twins, further refining the predictive and diagnostic capabilities of the models. The ML algorithms used include Logistic Regression (LR), Support Vector Classifier (SVC), K-Nearest Neighbours (KNN), Naive Bayes (NB), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), Neural Network (NN), AdaBoost (AB), Bagging (Ba), Extra Trees (ET), and XGBoost (XGB). …”
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