Co-construction with deathbots: a form of existentialist practice by Zhenxing Zhang, Donghui Dou, Xiaocen Liu

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Highly Accurate Numerical Method for Solving Fractional Differential Equations with Purely Integral Conditions by Hany M. Ahmed

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Highly accurate method for solving forced Duffing equations with integral boundary conditions by H. M. Ahmed

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SOURCES OF DIFFERENCES IN CALCULATIONS AND EXPERIMENTAL TEST RESULTS OF FATIGUE LIFE OF STRUCTURAL ELEMENTS by Józef SZALA, Bogdan LIGAJ, Grzegorz SZALA

“…The mentioned analysis was illustrated with examples of fatigue life tests performed in the Machine Design Department of the University of Technology and Agriculture within the research grant no. 2221/B/T02/2010/39 financed by The Ministry of Science and Higher Education and National Science Centre.…”
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Application of Generative Adversarial Nets (GANs) in Active Sound Production System of Electric Automobiles by Kai Liang, Haijun Zhao

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ON CONCEPTUAL APPROACHES TO DIGITAL TRANSFORMATION OF THE NATIONAL ECONOMY OF BELARUS by D. M. Krupsky

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The role and prognostic value of PANoptosis-related genes in skin cutaneous melanoma by Huijing Feng, Linzi Jia, Yanan Ma, Pengmin Liu, Xiaoling Yang, Lina Hu, Kai Xu, Fan Yang, Dongfeng Zhang, Jian Li, Qi Mei, Fei Han

“…Prognostic genes for SKCM were derived using Cox analysis and machine learning algorithms, leading to the construction and validation of a prognostic model. …”
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Russian Association of Endocrinologists expert consensus document on initiation and intensification of antyhyperglycaemic therapyin type 2 diabetes mellitus by Ivan Ivanovich Dedov, Marina Vladimirovna Shestakova, Alexander Sergeevich Ametov, Mikhail Borisovich Antsiferov, Gagik Radikovich Galstyan, Alexander Yur'evich Mayorov, Ashot Musaelovich Mkrtumyan, Nina Alexandrovna Petunina, Olga Yur'evna Sukhareva

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Emergency Department Blood Pressure Management in Type B Aortic Dissection: An Analysis with Machine Learning by Nelson Chen, Jessica V. Downing, Jacob Epstein, Samira Mudd, Angie Chan, Sneha Kuppireddy, Roya Tehrani, Isha Vashee, Emily Hart, Emily Esposito, Rose Chasm, Quincy K. Tran

“…We used random forest (RF) algorithms, a machine-learning tool that uses clusters of decision trees to predict a categorical outcome, to identify predictors of achieving HR and SBP goals prior to ED departure, defined as the time point at which patients left the referring ED to come to our institution. …”
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Developing a molecular diagnostic model for heatstroke-induced coagulopathy: a proteomics and metabolomics approach by Qingbo Zeng, Qingwei Lin, Longping He, Lincui Zhong, Ye Zhou, Xingping Deng, Nianqing Zhang, Qing Song, Qing Song, Jingchun Song, Jingchun Song

“…Functional annotation and pathway enrichment analyses were performed using the GO and KEGG databases, and machine learning models were developed using candidate proteins selected by LASSO and Boruta algorithms to diagnose HSIC. Finally, bioinformatic analysis was used to integrate the results of proteomics and metabolomics to find the potential mechanisms of HSIC.ResultsA total of 41 patients participated in the study, with 11 cases in the HSIC group and 30 cases in the NHSIC group. …”
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Wireless rechargeable sensor networks with separable charger array by Chengjie Xu, Rei-Heng Cheng, Tung-Kuang Wu

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Use of a convolutional neural network for direct detection of acid-fast bacilli from clinical specimens by Paul English, Muir J. Morrison, Blaine Mathison, Elizabeth Enrico, Ryan Shean, Brendan O'Fallon, Deven Rupp, Katie Knight, Alexandra Rangel, Jeffrey Gilivary, Amanda Vance, Haleina Hatch, Leo Lin, David P. Ng, Salika M. Shakir

“…A machine learning computer vision model was trained using 11,411 annotated organisms across 109 WSI. Model predictions were correlated with final culture-confirmed results. …”
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Breast tumors from ATM pathogenic variant carriers display a specific genome-wide DNA methylation profile by Nicolas M. Viart, Anne-Laure Renault, Séverine Eon-Marchais, Yue Jiao, Laetitia Fuhrmann, Sophia Murat El Houdigui, Dorothée Le Gal, Eve Cavaciuti, Marie-Gabrielle Dondon, Juana Beauvallet, Virginie Raynal, Dominique Stoppa-Lyonnet, Anne Vincent-Salomon, Nadine Andrieu, Melissa C. Southey, Fabienne Lesueur

“…Moreover, using three different deep learning algorithms (logistic regression, random forest and XGBoost), we identified a set of 27 additional biomarkers predictive of ATM status, which could be used in the future to provide evidence for or against pathogenicity in ATM variant classification strategies. …”
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A machine learning-based screening model for the early detection of prostate cancer developed using serum microRNA data from a mixed cohort of 8,741 participants by Cong Lai, Zhensheng Hu, Zhuohang Li, Zhikai Wu, Kuiqing Li, Lin Li, Hongze Liu, Juanyi Shi, Yi Zhou, Kewei Xu, Cheng Liu

“…Six machine learning algorithms were employed to develop a screening model for PCa using the training dataset. …”
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Exploring the Global and Regional Factors Influencing the Density of <i>Trachurus japonicus</i> in the South China Sea by Mingshuai Sun, Yaquan Li, Zuozhi Chen, Youwei Xu, Yutao Yang, Yan Zhang, Yalan Peng, Haoda Zhou

“…Leveraging advanced machine learning algorithms and causal inference, our robust experimental design uncovered nine key global and regional factors affecting the distribution of <i>T. japonicus</i> density. …”
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CECT-Based Radiomic Nomogram of Different Machine Learning Models for Differentiating Malignant and Benign Solid-Containing Renal Masses by Qian L, Fu B, He H, Liu S, Lu R

“…Radiomic features were extracted from the arterial, venous and delayed phases and further analysed by dimensionality reduction and selection. Four mainstream machine learning algorithm training models, namely, support vector machine (SVM), k-nearest neighbour (kNN), light gradient boosting (LightGBM) and logistic regression (LR), were constructed to determine the best classifier model. …”
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MOIRA-UNIMORE Bearing Data Set for Independent Cart Systems by Abdul Jabbar, Marco Cocconcelli, Gianluca D’Elia, Davide Borghi, Luca Capelli, Jacopo Cavalaglio Camargo Molano, Matteo Strozzi, Riccardo Rubini

“…The primary objective is to advance research in machine health monitoring, predictive maintenance, and stochastic modeling by providing the first data set of its kind. …”
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Exploring the role of mitochondrial metabolism and immune infiltration in myocardial infarction: novel insights from bioinformatics and experimental validation by Jingyi Hou, Jingyi Hou, Jingyi Hou, Lihan Wang, Lihan Wang, Naiqiang Zhu, Xueli Li

“…A protein-protein interaction (PPI) network of mitoDEGs was constructed, and hub mitoDEGs associated with MI were identified using CytoHubba and molecular complex detection (MCODE) algorithms. Transcription factor (TF) and microRNA (miRNA) targets of hub mitoDEGs were predicted using iRegulon and miRWalk plug-ins, respectively, and a regulatory network involving TFs, hub mitoDEGs, and miRNA was established. …”
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Clinician Attitudes and Perceptions of Point-of-Care Information Resources and Their Integration Into Electronic Health Records: Qualitative Interview Study by Marlika Marceau, Sevan Dulgarian, Jacob Cambre, Pamela M Garabedian, Mary G Amato, Diane L Seger, Lynn A Volk, Gretchen Purcell Jackson, David W Bates, Ronen Rozenblum, Ania Syrowatka

“…Some recommended that further integration would allow us to leverage existing POCI tool features, such as chatbots and knowledge links, as well as aspects of artificial intelligence and machine learning, such as predictive algorithms and personalized alert systems, to enhance EHR functionality. …”
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Unveiling lipoprotein subfractions signature in high-FNPO PCOS: implications for PCOM diagnosis and risk assessment using advanced machine learning models by Xueqi Yan, Ziyi Yang, Hui Zhao, Gengchen Feng, Shumin Li, Yimeng Li, Yu Sun, Jinlong Ma, Han Zhao, Xueying Gao, Shigang Zhao

“…Ten machine learning algorithms and recursive feature elimination with logistic regression were used to construct the effective model to predict PCOM based on the new guideline. …”
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