Predicting the delisted companies of Tehran Stock Exchange using machine learning based algorithms by Aminollah Zarghami, Meysam Doaei, Abtin Boostani

“…They were present in the stock market in the second group and were selected by systematic elimination method. Then, with data mining techniques, which are among the most efficient and up-to-date models of artificial intelligence, and with the help of multi-layered perceptron neural network classifiers, decision tree, and Bayesian theory classifiers, stock delisted companies have been predicted.Findings: The findings show that the Bayesian classifier had the best performance and the multilayer perceptron neural network was in the second place and the decision tree classifier was in the third place.Originality/Value: Little research has been done in the field of predicting delisted companies from the Iran capital market. …”
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Acromegaly: Is earlier diagnosis possible? Exploration of a screening algorithm to select high-risk patients by Tessa N.A. Slagboom, David de Jong, Peter H. Bisschop, Madeleine L. Drent

“…Purpose: Given the ongoing need to reduce the delay in diagnosis of acromegaly, the aim of the current study was to develop a screening algorithm that: finds as many patients as possible who have already been diagnosed with acromegaly (=sensitivity), while identifying a limited number of additional patients who are at risk for acromegaly as a proxy for specificity. Methods: CTcue data mining software (version 4.7, IQVIA Inc., USA) was used to develop a screening algorithm. …”
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Development of Diagnostic Biomarkers for Detecting Diabetic Retinopathy at Early Stages Using Quantitative Proteomics by Jonghwa Jin, Hophil Min, Sang Jin Kim, Sohee Oh, Kyunggon Kim, Hyeong Gon Yu, Taesung Park, Youngsoo Kim

“…First, to identify biomarker candidates that are specifically expressed in human vitreous, we performed data-mining on both previously published DR-related studies and our experimental data; 96 proteins were then selected. …”
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Predicting Solar Energetic Particle Events with Time Series Shapelets by Omar Bahri, Peiyu Li, Soukaïna Filali Boubrahimi, Shah Muhammad Hamdi

“…We leverage some of the most recent advances in time series data mining, such as shapelets and the matrix profile, to propose a simple and easily understandable prediction approach. …”
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Cell-Specific Regulation of Inflammatory Cytokines and Acute-Phase Proteins by the Glucocorticoid Receptor by Rebecca Winkler, Hong Lu

“…Background. Literature and data mining found abnormal induction of chemokine (C-X-C motif) ligand 1 (CXCL1) and CXCL8 and down-regulation of CXCL2 in inflammatory liver diseases. …”
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Predicting the Botanical Origin of Honeys with Chemometric Analysis According to Their Antioxidant and Physicochemical Properties by Anna Maria Kaczmarek, Małgorzata Muzolf-Panek, Jolanta Tomaszewska-Gras, Piotr Konieczny

“…Also Principal Component Analysis (PCA) and Cluster Analysis (CA) were performed as initial steps of data mining. The datasets consisted of 72 honey samples (false acacia, rape, buckwheat, honeydew, linden, nectar-honeydew and multifloral) obtained from different regions of Poland and collected between April 2014 and November 2016. …”
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Evaluation of Sharia-based Sustainability Reporting Framework Influenced by the Emergence of Metaverse Axes in Accounting by Hossein Keshavarzi Nejhad, Maryam Shahri, Vahid Oskou, Mohammad Reza Abdoli

“…In the quantitative part, the result indicates the determination of the development of the data mining process in accounting analysis as the most central influence on the dimension of adherence to Sharia ethics in sustainability reporting. …”
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Metabolic and epigenetic regulation of macrophage polarization in atherosclerosis: Molecular mechanisms and targeted therapies by Pinglian Yang, Xiaoling Rong, Zhechang Gao, Jiaojiao Wang, Zhiping Liu

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Predicting high sensitivity C-reactive protein levels and their associations in a large population using decision tree and linear regression by Somayeh Ghiasi Hafezi, Toktam Sahranavard, Alireza Kooshki, Marzieh Hosseini, Amin Mansoori, Elham Amir Fakhrian, Helia Rezaeifard, Mark Ghamsary, Habibollah Esmaily, Majid Ghayour-Mobarhan

“…This study was conducted on a population of 9704 males and females aged 35 to 65 years recruited from the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) cohort study. We utilized a data mining approach to construct a predictive model of hs-CRP measurements, employing the DT methodology. …”
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Tuberculosis and COVID-19: Lessons from the Past Viral Outbreaks and Possible Future Outcomes by Radu Crisan-Dabija, Cristina Grigorescu, Cristina-Alice Pavel, Bogdan Artene, Iolanda Valentina Popa, Andrei Cernomaz, Alexandru Burlacu

“…The PubMed electronic database was systematically searched for relevant articles linking TB, influenza, and SARS-CoV viruses and subsequently assessed eligibility according to inclusion criteria. Using a data mining approach, we also queried the COVID-19 Open Research Dataset (CORD-19). …”
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Anomaly Usage Behavior Detection Based on Multi-Source Water and Electricity Consumption Information by Wenqing Zhou, Chaoqiang Chen, Qin Yan, Bin Li, Kang Liu, Yingjun Zheng, Hongming Yang, Hui Xiao, Sheng Su

“…Specifically, the correlation between water and electricity usage of residential customers is analyzed based on real metering data and the use of the Copula distribution function, followed by the integration of two innovative data mining techniques to form an anomaly detection framework. …”
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Exploring diazotrophic diversity: unveiling Nif core distribution and evolutionary patterns in nitrogen-fixing organisms by Bruno Thiago de Lima Nichio, Roxana Beatriz Ribeiro Chaves, Fábio de Oliveira Pedrosa, Roberto Tadeu Raittz

“…Using this Nif database and a data mining strategy, we extended our analysis to 711 species and found that 544 contain the Nif core. …”
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A Multiple-detection-heads Machine Learning Algorithm for Detecting White Dwarfs by Jiangchuan Zhang, Yude Bu, Mengmeng Zhang, Duo Xie, Zhenping Yi

“…In recent years, machine learning has played a significant role in astronomical data mining, due to its speed, real time, and precision. …”
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Post-marketing safety surveillance for the recombinant zoster vaccine (Shingrix), vaccine adverse event reporting system, United States, October 2017–April 2024 by Yamin Shu, Wenxin Cheng, Xucheng He, Liu Huang, Wei Chen, Qilin Zhang

“…The empirical Bayesian data mining was employed to identify potential disproportionalities in reporting. …”
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The Underlying Molecular Basis and Mechanisms of Venous Thrombosis in Patients with Osteomyelitis: A Data-Driven Analysis by Peisheng Chen, Yinhuan Liu, Xiaofeng Lin, Bin Yu, Bin Chen, Fengfei Lin

“…Conclusion. This is the first data-mining study to explore shared signatures between OM and VTE by the integrated bioinformatic approach, which can help uncover potential biomarkers and therapeutic targets of OM-related VTE.…”
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An Experimental Investigation on the Relationship between MS Frequency Response and Coal and Gas Outburst by Quanjie Zhu, Qingsong Li, Yu Feng, Xianwei Heng, Shaoquan Li, Tao Yang

“…Microseismic (MS) frequency response is an important part of high-efficiency data mining to achieve the aim of coal and gas outburst (CGOB) early warning. …”
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Adverse drug events (ADEs) risk signal mining related to eculizumab based on the FARES database by Xi-Feng Wang, Lu-Ri Bao, Ta-La Hu, Rui-Feng Xu, Wu-Niri Gao, Jing-Yuan Wang, Jian-Rong Zhao, Zhen-Li Fu, Shu-Fang Wang, Yan Meng

“…The current study was conducted to assess real-world adverse events (AEs) associated with eculizumab through data mining of the FDA Adverse Event Reporting System (FAERS).MethodsDisproportionality analyses, including Reporting Ratio Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS) algorithms were used to quantify the signals of eculizumab-associated AEs.ResultsA total of 46,316 eculizumab-related ADEs reports were identified by analyzing 19,418,776 reports in the U.S. …”
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Therapeutic target genes and regulatory networks of gallic acid in cervical cancer by Zhixi You, Ye Lei, Yongkang Yang, Zhihui Zhou, Xu Chao, Keyi Ju, Songyi Wang, Yuanyuan Li, Yuanyuan Li

“…The upstream 13 miRNAs, 4 lncRNA, and 42 circRNAs were detected and used to construct a lncRNA/circRNA-miRNA-mRNA-pathway regulatory network.ConclusionThis study identified candidate genes and the regulatory networks underlying the therapeutic effects of GA on CC using GA data mining methods, thus establishing a theoretical basis for targeted therapy of CC.…”
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Network pharmacology-based screening of the active ingredients and mechanisms of Cymbaria daurica against diabetes mellitus by Ruyu Shi, Dongxue Chen, Mingyue Ji, Baochang Zhou, Ziyan Zhang, Chunhong Zhang, Minhui Li

“…In this study, the potential mechanism of C. daurica against type 2 diabetes mellitus (T2DM) was postulated via pharmacological network analysis. Based on data mining techniques involving topological parameters, gene ontology, and pathway enrichment, we established a compound-target, protein-protein interaction, and target-pathway network to identify central targets and pathways. …”
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THE SOLANUM TUBEROSUM KNOWLEDGE BASE: THE SECTION ON MOLECULAR-GENETIC REGULATION OF METABOLIC PATHWAYS by T. V. Ivanisenko, O. V. Saik, P. S. Demenkov, V. K. Khlestkin, E. K. Khlestkina, N A. Kolchanov, V. А. Ivanisenko

“…Effective access to knowledge distributed over such a multitude of non-formalized natural language textual sources requires the use of special computer-assisted intelligent methods of data mining (text-mining). However, in the literature, there is no data on the application of intellectual methods of automatic knowledge extraction from publications on agricultural crops, such as potato. …”
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