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  1. 3521

    Construction of a sleep staging prediction model for obstructive sleep apnea patients based on hypoxia parameters by YANG Mengdie,PENG Cheng,CUI Yiran,XU Shaorong,WANG Yan

    Published 2025-06-01
    “…The ANN model was constructed using a feed-forward structure incorporating a multilayer perceptron(MLP)with a back-propagation algorithm. Predictive performance was assessed using receiver operating characteristic(ROC)curves.Results Compared with the hypoxia parameters in NREM stage,e-minSpO2 and r.DSpO2 were lower,and ΔSpO2,d.DSpO2,ODR,ORR,T90,d.T90,r.T90,and ST90,d.ST90,r.ST90 were higher in REM stage(P<0.05). …”
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    Article
  2. 3522

    Pan-cancer predictive survival model development and evaluation using electronic health record and genetic data across 10 cancer types by Jurgita Gammall, Alvina G. Lai

    Published 2025-05-01
    “…We compare the performance of different machine learning algorithms and assess the added value of genetic information in cancer prognosis. …”
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  3. 3523
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    How Predictable Is Electric Vehicle Adoption? Exploring the Broader Role of Renewables in Transportation Using a Data-Driven Approach by Simona-Vasilica Oprea, Adela Bara

    Published 2025-01-01
    “…Equally important is the capacity to predict the likelihood of EV adoption. A classification model is proposed, embedding several cutting-edge classifiers. …”
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    Article
  5. 3525

    Development and validation of a machine learning-based survival prediction model for Asian glioblastoma patients using the SEER database and Chinese data by Denglin Li, Luxin Zhang, Lifei Xu, Renhe Zhai, Hanyu Gao, Junlan Gao, Minghai Wei, Ningwei Che, Yeting He

    Published 2025-08-01
    “…Our study attempted to investigate the independent predictors of overall survival (OS) and cancer-specific survival (CSS) in Asian patients with glioblastoma and establish predictive models for the OS and CSS of Asian patients with glioblastoma based on the machine learning algorithms. …”
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  8. 3528

    Crude Oil and Hot-Rolled Coil Futures Price Prediction Based on Multi-Dimensional Fusion Feature Enhancement by Yongli Tang, Zhenlun Gao, Ya Li, Zhongqi Cai, Jinxia Yu, Panke Qin

    Published 2025-06-01
    “…In addition, the significance and stability of the model performance were verified by statistical methods such as a paired t-test and ANOVA analysis of variance. This MDFFE algorithm offers a robust and practical approach for predicting commodity futures prices. …”
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  9. 3529
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    Variable Step-Size Hybrid Filtered-x Affine Projection Generalized Correntropy Algorithm for Active Noise Control by Zhaoqing Mu, Ying Gao, Xinyu Guo, Shifeng Ou

    Published 2025-03-01
    “…To showcase the practical effectiveness of the proposed algorithm, noisy audio from a real construction site was used for noise reduction control. …”
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  11. 3531

    Predicting the outcome of psychological treatments for borderline personality disorder and posttraumatic stress disorder: a machine learning approach to predict long-term outcome o... by Jakob Blaß, Benjamin Iffland, Philipp Herzog, Tim Kaiser, Thomas Elbert, Carolin Steuwe

    Published 2025-12-01
    “…A cross-validated genetic algorithm was used to detect baseline predictors of change in PTSD symptoms.Results: In the NET group higher education, more baseline PTSD symptoms, more traumatic experiences, fewer baseline BPD symptoms, and not taking antipsychotic medication predicted better treatment outcome. …”
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    Building a Computer Vocational Guidance System for Graduates of Secondary Educational Institutions Based on a Genetic Algorithm by A. P. Sergushicheva, E. N. Davydova

    Published 2020-06-01
    “…The purpose of the article is to present the results of a study on the development of a genetic algorithm to solve the problems of career guidance for graduates of secondary educational institutions and to verify the possibility of its implementation in a computer system. …”
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    Stunting Prediction Modeling in Toddlers Using a Machine Learning Approach and Model Implementation for Mobile Application by Eko Abdul Goffar, Rosa Eliviani, Lili Ayu Wulandhari

    Published 2025-06-01
    “…The literature review section discusses the factors that influence stunting, and these factors are used as features to build a stunting prediction model. Then the features were used to build a model with three machine learning algorithms Extreme Gradient Boosting (XGBoost), Random Forest, and K-Nearest Neighbor (KNN) to build and evaluate models that predict stunting. …”
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