Investigation of the Regularities of the Influence of Meteorological Factors on Avalanches in Eastern Kazakhstan by Marzhan Rakhymberdina, Natalya Denissova, Yerkebulan Bekishev, Gulzhan Daumova, Milan Konečný, Zhanna Assylkhanova, Azamat Kapasov

“…The results emphasize the need for an integrated approach to avalanche forecasting that accounts for the multi-parametric interactions of meteorological factors, and may contribute to the improvement of avalanche risk monitoring and mitigation systems in mountain regions.…”
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The Systemic Immune‐Inflammation Index and Its Association With Biologic Therapy Switching and Response in Psoriasis by Gregg Murray, Niamh Kearney, Conor Smith, Kieran Carty, Yasmine Safta, Olwyn Conlon, Brian Kirby, Ali Alsharqi

“…Integrating SII into psoriasis treatment algorithms may enable clinicians to identify high‐risk patients early, optimise biologic selection, and improve long‐term outcomes. …”
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Postmarketing safety evaluation of pemetrexed using FAERS and JADER databases by Luo Lv, Xiangyang Wu, Yubo Ren, Yuli Guo, Haixiong Wang, Xiaofang Li

“…Disproportionality analysis was performed using four algorithms: Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS). …”
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Cell death-related signature genes: risk-predictive biomarkers and potential therapeutic targets in severe sepsis by Yanan Li, Yuqiu Tan, Zengwen Ma, Zengwen Ma, Weiwei Qian, Weiwei Qian

“…GSEA analysis revealed key immune pathways in which SeDGs may be involved. In addition, unsupervised clustering analysis revealed that SeALAR patients could be classified into two molecular subtypes, providing a new direction for the development of individualized immunotherapy strategies. …”
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Machine learning analysis of FOSL2 and RHoBTB1 as central immunological regulators in knee osteoarthritis synovium by Kun Gao, Zhenyu Huang, Zhouwei Liao, Yanfei Wang, Dayu Chen

“…We employed several machine learning algorithms, including least absolute shrinkage and selection operator and support vector machine–recursive feature elimination, to screen for key genes. …”
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Pediatric sepsis phenotypes for enhanced therapeutics: An application of clustering to electronic health records by Ioannis Koutroulis, Tom Velez, Tony Wang, Seife Yohannes, Jessica E. Galarraga, Joseph A. Morales, Robert J. Freishtat, James M. Chamberlain

“…Using feature sets used in related clustering studies, LCA and K‐means algorithms were used to derive 4 distinct phenotypic pediatric sepsis segmentations. …”
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Efficient evidence selection for systematic reviews in traditional Chinese medicine by Yizhen Li, Zhe Huang, Zhongzhi Luan, Shujing Xu, Yunan Zhang, Lin Wu, Darong Wu, Dongran Han, Yixing Liu

“…Methods We integrated an established deep learning model (Evi-BERT combined rule-based method) with Boolean logic algorithms and an expanded retrieval strategy to automatically and accurately select potential evidence with minimal human intervention. …”
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The application of super-resolution ultrasound radiomics models in predicting the failure of conservative treatment for ectopic pregnancy by Mingyan Zhang, Junfa Sheng

“…Abstract Background Conservative treatment remains a viable option for selected patients with ectopic pregnancy (EP), but failure may lead to rupture and serious complications. Currently, serum β-hCG is the main predictor for treatment outcomes, yet its accuracy is limited. …”
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Integrated transcriptome analysis and combinatorial machine learning to construct a homeostatic model of acetylation for ccRCC and validate the key gene GCNT4 by Baohua Zhu, Ziyang Mo, Yi Bao, Xinxin Gan, Linhui Wang

“…Ten machine learning algorithms and their 101 combinations were used to analyze the prognostic significance of acetylation-related differentially expressed genes (DEGs) and to construct a prognostic risk model. …”
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Multi-Omics Identification of <i>Fos</i> as a Central Regulator in Skeletal Muscle Adaptation to Long-Term Aerobic Exercise by Chaoyang Li, Xinyuan Zhu, Yi Yan

“…Key feature genes were screened using Lasso regression, SVM-RFE, and Random Forest machine learning algorithms, validated by RT-qPCR, and refined through PPI network analysis. …”
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Identification of key genes and immune infiltration mechanisms in limb ischemia-reperfusion injury: a bioinformatics and experimental study by Qiyun Shi, Taotao Tian, Yanfeng Li

“…Random forest, LASSO regression, algorithms identified feature genes, validated in a rat limb IRI model using RT-qPCR, and histology. …”
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Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics by Yi Ding, Zhaiyue Xu, Wenjing Hu, Peng Deng, Mian Ma, Jiandong Wu

“…Dual checkpoint blockade or T-cell-rejuvenation strategies may benefit CS2 tumours, while metabolic inhibitors could prove effective in CS3. …”
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Integrating microplastic research in sustainable agriculture: Challenges and future directions for food production by Marcelo Illanes, María-Trinidad Toro, Mauricio Schoebitz, Nelson Zapata, Diego A. Moreno, María Dolores López-Belchí

“…In addition, their interaction with high temperatures may induce increased oxidative stress, whereas drought conditions can adversely affect vegetative growth. …”
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Development and validation of an explainable machine learning prediction model of hemorrhagic transformation after intravenous thrombolysis in stroke by Yanan Lin, Yan Li, Yayin Luo, Jie Han

“…We utilized the Random Forest (RF), Multilayer Perceptron (MLP), Adaptive Boosting (AdaBoost), and Gaussian Naive Bayes (GauNB) algorithms to develop ML-HT models. The models' predictive performance was evaluated using confusion matrix (including accuracy, precision, recall, and F1 score), and discriminative analysis (area under the receiver-operating-characteristic curve, ROC-AUC) in the original cohort, followed by validation in an independent external cohort. …”
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Quantifying leaf symptoms of sorghum charcoal rot in images of field‐grown plants using deep neural networks by Emmanuel M. Gonzalez, Ariyan Zarei, Sebastian Calleja, Clay Christenson, Bruno Rozzi, Jeffrey Demieville, Jiahuai Hu, Andrea L. Eveland, Brian Dilkes, Kobus Barnard, Eric Lyons, Duke Pauli

“…The objective of this work was to implement various machine learning algorithms to evaluate their ability to accurately detect and quantify CRS in red‐green‐blue images of sorghum plants exhibiting symptoms of infection. …”
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Using fishery-related data, scientific expertise, and machine learning to improve marine habitat mapping in northeastern Mediterranean waters by Loukas Katikas, Sofia Reizopoulou, Paraskevi Drakopoulou, Vassiliki Vassilopoulou

“…High spatial resolution in marine habitat maps is of utmost importance, as it may encompass more detail in imagery and reveal important biotopes. …”
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A deep contrastive learning-based image retrieval system for automatic detection of infectious cattle diseases by Veerayuth Kittichai, Morakot Kaewthamasorn, Apinya Arnuphaprasert, Rangsan Jomtarak, Kaung Myat Naing, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang

“…Intra- and inter-rater variation is frequently imposed on by technicians who are underqualified and unexperienced. Alternatively, algorithms could support local employees in tracking disease transmission and quick action, especially in Thailand where this cattle disease is common. …”
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Natural Language Processing and Machine Learning Techniques for Analyzing Conversations About Nutritional Yeasts in the United States and France: Retrospective Social Media Listeni... by Jean-François Jeanne, Joelle Malaab, Antoine Vanhove, Florian Mourey, Manissa Talmatkadi, Stéphane Schück

“…Data cleaning and filtering were done using natural language processing methods and specific algorithms. Biterm topic modeling was applied to identify the most frequently discussed topics. …”
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Mental health promotion in disasters: exploring the synergy of artificial intelligence, spirituality, and psychology: a SWOT analysis by Rasoul Fattahipour, Simintaj Sharififar, Fatemeh Teymouri, Maryam Azizi, Milad Ahmadi Marzaleh

“…Abstract Background Natural and man-made disasters affect people's lives yearly and may lead to suffering, poverty, and psychological challenges. …”
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Diagnostic Possibilities of Optical Coherent Tomography of the Retina during Compression in the Chiasm-Sellar Region by N. A. Gavrilova, E. E. Ioyleva, N. S. Gadzhieva, O. E. Tishchenko, N. Y. Kutrovskaya, A. V. Kuz’mina, A. V. Zinov’eva

“…In this regard, it is necessary to conduct further studies that will reveal the informative OСT-diagnostic criteria for compression in the chiasm-sellar region, develop diagnostic algorithms taking into account the type of tumor, the presence of concomitant pathology. …”
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