Prediction of Liquefaction-Induced Lateral Displacements Using Hybrid GBRT and EOA by Arash Ziaie, Bahareh Mehdizadeh, Farzad Safi Jahanshahi, Nazanin Ahmadi, Ali Reza Ghanizadeh

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A New Strategy to Modify Hopfield by Using XOR Operation by Rusul Hussein Hasan

“…This paper proposes a new strategy for designing Hopfield based on XOR operation; A new strategy is proposed to solve these limitations by suggesting a new algorithm in the Hopfield network design, this strategy will increase the performance of Hopfield by modifying the architecture of the network, the training and the convergence phases, the proposed strategy based on size of pattern but will avoid learning similar pattern many time, whereas the new strategy XOR shows tolerance in the presence of noise-distorted patterns, infinite storage capacity and pattern inverse value. …”
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Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction by Jingjing Chen, Dan Zhang, Chengxiu Zhu, Lin Lin, Kejun Ye, Ying Hua, Mengjia Peng

“…Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”
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Interpretable machine learning for early predicting the risk of ventilator-associated pneumonia in ischemic stroke patients in the intensive care unit by Heshan Cao, Junying Wei, Ping Hua, Songran Yang, Songran Yang

“…BackgroundThe incidence of ventilator-associated pneumonia (VAP) in ischemic stroke (IS) patients is linked to a variety of detrimental outcomes. …”
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CytoLNCpred-a computational method for predicting cytoplasm associated long non-coding RNAs in 15 cell-lines by Shubham Choudhury, Naman Kumar Mehta, Gajendra P. S. Raghava

“…All models in this study were trained using five-fold cross validation and tested on an validation dataset. …”
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Prognosis and immune landscape of bladder cancer can be predicted using a novel miRNA signature associated with cuproptosis by Zhilei Zhang, Fang Liu, Yongbo Yu, Fei Xie, Tao Zhu

“…Results We developed a panel of eight cuproptosis-associated miRNAs to serve as a prognostic signature. …”
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Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration by Maoqiang Lin, Maoqiang Lin, Shaolong Li, Yabin Wang, Yabin Wang, Guan Zheng, Guan Zheng, Fukang Hu, Fukang Hu, Qiang Zhang, Qiang Zhang, Pengjie Song, Haiyu Zhou, Haiyu Zhou

“…Additionally, drug regulatory networks and ceRNA networks were constructed, revealing potential therapeutic drugs and post-transcriptional regulatory mechanisms.ConclusionWe developed and validated a lymphatics-associated genes diagnostic model by machine learning algorithms that effectively identify IVDD patients. …”
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An optimized support vector machine for lung cancer classification system by Mayowa O. Oyediran, Olufemi S. Ojo, Ibrahim A. Raji, Abidemi Emmanuel Adeniyi, Oluwasegun Julius Aroba, Oluwasegun Julius Aroba

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Satisfaction with Research-Based Learning and Academic Performance by Big Data Analysis by Gabriela Torres-Delgado, Sofía Ramos-Pulido, Neil Hernández-Gress

“…In total, 342 teachers were trained and received accreditation. The analyses incorporated non-conventional data science methods such as correlation analysis, principal component analysis, and unsupervised learning utilizing the Density-Based Spatial Clustering Application with Noise algorithm. …”
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Enhancing Education with Machine Learning: Predicting Student Readability Scores by Claire Bell

“…The research leverages a dataset of 1,000 English texts to evaluate and compare the performance of RFC, the Sooty Tern Optimization Algorithm (STOA), and the Gold Rush Optimizer (GRO) in predicting readability ratings. …”
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Identification of novel potential biomarkers using bulk RNA and single cells to build a neural network model for diagnosis of liver cancer by Yingzheng Gao, Jiahao Chen, Weidong Du

“…We used multiple machine algorithms to find hub genes related to liver cancer, and constructed new artificial neural network models based on their transcriptome expression patterns to assist in the diagnosis of liver cancer. …”
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Statistical Evaluation of Smartphone-Based Automated Grading System for Ocular Redness Associated with Dry Eye Disease and Implications for Clinical Trials by Rodriguez JD, Hamm A, Bensinger E, Kerti SJ, Gomes PJ, Ousler III GW, Gupta P, De Moraes CG, Abelson MB

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Development and validation of a machine learning-based risk prediction model for stroke-associated pneumonia in older adult hemorrhagic stroke by Yi Cao, Yi Cao, Haipeng Deng, Shaoyun Liu, Xi Zeng, Yangyang Gou, Weiting Zhang, Yixinyuan Li, Hua Yang, Min Peng

“…ObjectiveTo develop and validate a machine learning (ML)-based model for predicting stroke-associated pneumonia (SAP) risk in older adult hemorrhagic stroke patients.MethodsA retrospective collection of older adult hemorrhagic stroke patients from three tertiary hospitals in Guiyang, Guizhou Province (January 2019–December 2022) formed the modeling cohort, randomly split into training and internal validation sets (7:3 ratio). …”
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INTELLECTUAL INFORMATION TECHNOLOGIES IN AUTOMATED SYSTEMS OF MANAGEMENT OF TECHNOLOGICAL PROCESSES by Svetlana Vyacheslavovna Shilkina, Alla Alexandrovna Gusarova

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Segmentation of Leukoaraiosis on Noncontrast Head CT Using CT‐MRI Paired Data Without Human Annotation by Wi‐Sun Ryu, Jae W. Song, Jae‐Sung Lim, Ju Hyung Lee, Leonard Sunwoo, Dongmin Kim, Dong‐Eog Kim, Hee‐Joon Bae, Myungjae Lee, Beom Joon Kim

“…We developed and validated a deep learning algorithm for LA segmentation using CT‐MRIFLAIR paired data from a multicenter Korean registry and tested it in a US dataset. …”
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Explainable machine learning algorithms to identify predictors of intention to use family planning among women of reproductive-age in Ethiopia: Evidence from the Performance Monito... by Agmasie Damtew Walle, Shimels Derso Kebede, Jibril Bashir Adem, Tewodros Desalegn Nebi, Daniel Niguse Mamo, Sudi Jemal Wado, Ermias Bekele Enyew

“…Thus, using explainable machine learning algorithms, this study aimed to identify the key determinants of intention to use FP among women of reproductive age in Ethiopia.Methods Secondary data from the Ethiopian Performance Monitoring and Accountability 2021 survey were analysed using R and Python on Google Colab. …”
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Calibrating multiplex serology for Helicobacter pylori by Emmanuelle A. Dankwa, Martyn Plummer, Daniel Chapman, Rima Jeske, Julia Butt, Michael Hill, Tim Waterboer, Iona Y. Millwood, Ling Yang, Christiana Kartsonaki

“…This study furthers our understanding of the applicability of classification algorithms to the context of serologic tests.…”
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Exercise-changed gut mycobiome as a potential contributor to metabolic benefits in diabetes prevention: an integrative multi-omics study by Yao Wang, Jiarui Chen, Yueqiong Ni, Yan Liu, Xiang Gao, Michael Andrew Tse, Gianni Panagiotou, Aimin Xu

“…With our established randomized controlled trial of exercise intervention in Chinese males with prediabetes (n = 39, ClinicalTrials.gov:NCT03240978), we investigated the dynamics of human gut mycobiome and further interrogated their associations with exercise-elicited outcomes using multi-omics approaches.Methods Clinical variations and biological samples were collected before and after training. …”
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Research on cause analysis and management of coal mine safety risk based on social network and bow-tie model by Guorui Su

“…Furthermore, the Apriori algorithm was applied to uncover hidden associations among gas safety risk factors, revealing critical compound relationships among factors such as inadequate safety management, insufficient inspections, high incidence of “three violations”, and poor safety education. …”
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Ecological Momentary Assessment of emotional dysregulation and outbursts among youth with ADHD: a feasibility study of a biomarker-driven predictive algorithm in the special educat... by Ripudaman (Zeeba) Singh, Janav Panchal, Sami Ali, Beth Krone, Isaac J. Wert, Mark Owens, Mark Stein, Maulik V. Shah

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