Showing 481 - 500 results of 1,436 for search '(((mode OR model) OR more) OR made) screening algorithm', query time: 0.33s Refine Results
  1. 481

    Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network by Xiaorong Li, Lijun Zhang, Dongchen Li, Dan Guo

    Published 2022-01-01
    “…In this paper, RNN (Recurrent Neural Network) algorithm is used to conduct an in-depth analysis of HR strategic decision-making and an HR strategic decision model is constructed for simulation. …”
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    Article
  2. 482

    Risk prediction model for overall survival in lung cancer based on inflammatory and nutritional markers by Hongqi Zhou, Weiyun Jin, Lindi Li, Xiangwen Nie, Weiwei Wu, Ran Chen, Qizhen Xie, Haixia Wu, Weiwei Jiang, Min Tang, Jinhai Wang, Maoyuan Wang

    Published 2025-08-01
    “…All patients were followed until death or a uniform administrative censoring point.LASSO logistic regression was employed to model the outcome as a binary classification (death within 1 year: yes/no).This study employed a small-sample modeling approach, initially using LASSO regression for feature selection and dimensionality reduction, followed by variance inflation factor and collinearity screening for secondary feature selection. …”
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  3. 483

    Comparing machine learning models for osteoporosis prediction in Tibetan middle aged and elderly women by Peng Wang, Qiang Yin, Kangzhi Ding, Huaichang Zhong, Qundi Jia, Zhasang Xiao, Hai Xiong

    Published 2025-03-01
    “…In test set, the order of AUC from highest to lowest is XGB (0.848), regression (0.801), Random Forest (0.772), SVM (0.755), OSTA (0.739), ANN (0.732). SVM and XGB algorithm models had better screening effect on osteoporosis than OSTA in middle-aged and elderly Tibetan residents in Tibet. …”
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    Article
  4. 484

    Interpretable model based on MRI radiomics to predict the expression of Ki-67 in breast cancer by Li Zhang, Qinglin Du, Mengyi Shen, Xin He, Dingyi Zhang, Xiaohua Huang

    Published 2025-04-01
    “…Combining the SHAP algorithm with the model improves its interpretability, which may assist clinicians in formulating more accurate treatment strategies.…”
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    Article
  5. 485

    Discovering New Tyrosinase Inhibitors by Using In Silico Modelling, Molecular Docking, and Molecular Dynamics by Kevin A. OréMaldonado, Sebastián A. Cuesta, José R. Mora, Marcos A. Loroño, José L. Paz

    Published 2025-03-01
    “…<b>Methods</b>: Four machine learning algorithms and topographical descriptors were tested for model construction. …”
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    Article
  6. 486

    External Validation of Persistent Severe Acute Kidney Injury Prediction With Machine Learning Model by Simone Zappalà, PhD, Francesca Alfieri, MS, Andrea Ancona, PhD, Antonio M. Dell’Anna, MD, Kianoush B. Kashani, MD, MS

    Published 2025-06-01
    “…The performance of the PersEA model, a boosted tree algorithm fed by hourly patient data via electronic health records to provide real-time psAKI predictions, was evaluated using specific metrics that penalize late alarms. …”
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    Article
  7. 487

    Machine learning modeling for the risk of acute kidney injury in inpatients receiving amikacin and etimicin by Pei Zhang, Qiong Chen, Jiahui Lao, Juan Shi, Jia Cao, Xiao Li, Xin Huang

    Published 2025-05-01
    “…Univariate analyses and the least absolute shrinkage and selection operator algorithm were used to screen risk factors and construct the model. …”
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    Article
  8. 488

    Comparison of machine learning models for mucopolysaccharidosis early diagnosis using UAE medical records by Aamna AlShehhi, Hiba Alblooshi, Ruba Fadul, Natnael Tumzghi, Amal Al Tenaiji, Mariam Al Harbi, Fatma Al-Jasmi

    Published 2025-08-01
    “…Using nested cross-validation, we trained different feature selection algorithms in combination with various ML algorithms and evaluated their performance with multiple evaluation metrics. …”
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    Article
  9. 489
  10. 490

    Iron Ore Information Extraction Based on CNN-LSTM Composite Deep Learning Model by Haili Chen, Mengxiang Xia, Yaping Zhang, Ruonan Zhao, Bingran Song, Yang Bai

    Published 2025-01-01
    “…The bands are subsequently screened by correlation analysis, successive projections algorithm (SPA), and competitive adaptive reweighted sampling (CARS), down to 50 dimensions using principal component analysis (PCA). …”
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    Article
  11. 491

    Development and Validation of an AI-Based Risk Prediction Model for Osteoporosis in Post-Menopausal Women by Juhi Deshpande, Chanchal Kumar Singh

    Published 2025-06-01
    “…Timely risk stratification remains challenging despite available screening tools. The aim is to develop and validate an AI-based predictive model for osteoporosis in postmenopausal women. …”
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    Article
  12. 492

    Comparison of Transfer Learning Model Performance for Breast Cancer Type Classification in Mammogram Images by Cahya Bagus Sanjaya, Muhammad Imron Rosadi, Moch. Lutfi, Lukman Hakim

    Published 2025-02-01
    “…Early detection of breast cancer is very important because there is a big chance of cure. Mammography screening makes it possible to detect breast cancer early. …”
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    Article
  13. 493

    Development of standard fuel models in boreal forests of Northeast China through calibration and validation. by Longyan Cai, Hong S He, Zhiwei Wu, Benard L Lewis, Yu Liang

    Published 2014-01-01
    “…Fuel model parameter sensitivity was analyzed by the Morris screening method. …”
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    Article
  14. 494

    Orga-Dete: An Improved Lightweight Deep Learning Model for Lung Organoid Detection and Classification by Xuan Huang, Qin Gao, Hanwen Zhang, Fuhong Min, Dong Li, Gangyin Luo

    Published 2025-07-01
    “…Lung organoids play a crucial role in modeling drug responses in pulmonary diseases. However, their morphological analysis remains hindered by manual detection inefficiencies and the high computational cost of existing algorithms. …”
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    Article
  15. 495

    Construction and Validation of Predictive Model to Identify Critical Genes Associated with Advanced Kidney Disease by Guangda Xin, Guangyu Zhou, Wenlong Zhang, Xiaofei Zhang

    Published 2020-01-01
    “…Differential expressed genes (DEGs) were identified and functional enrichment analysis. Machine learning algorithm-based prediction model was constructed to identify crucial functional feature genes related to ESRD. …”
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    Article
  16. 496

    T cell receptor signaling pathway subgroups and construction of a novel prognostic model in osteosarcoma by Huan Xu, Huimin Tao

    Published 2025-01-01
    “…Two hundred and seventy-two Differential expressed TCRGs were screened between two subclusters. A robust prognostic model were constructed. …”
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    Article
  17. 497

    CSCA-YOLOv8: A lightweight network model for evaluating drought resistance in mung bean. by Dongshan Jiang, Jinyang Liu, Haomiao Zhang, Wenxiang Liang, Ziqiu Luo, Wenlong An, Shicong Li, Xin Chen, Xingxing Yuan, Shangbing Gao

    Published 2025-01-01
    “…We also verified the excellent performance and generalization performance of the model using the collected MDD dataset. The final experimental results show that compared with the YOLOv8s baseline model, the number of parameters of our proposed algorithm is reduced by 24%, the floating point number is reduced by 35%, and the accuracy is improved by 2.52%, which supports the deployment on embedded edge devices with limited computing power. …”
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    Article
  18. 498

    Establishment of interpretable cytotoxicity prediction models using machine learning analysis of transcriptome features by You Wu, Ke Tang, Chunzheng Wang, Hao Song, Fanfan Zhou, Ying Guo

    Published 2025-03-01
    “…In summary, the models established in this research exhibit superior capacity to those of previous studies; these models enable accurate high-safety substance screening via cytotoxicity prediction across cell lines. …”
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    Article
  19. 499

    Constructing a fall risk prediction model for hospitalized patients using machine learning by Cheng-Wei Kang, Zhao-Kui Yan, Jia-Liang Tian, Xiao-Bing Pu, Li-Xue Wu

    Published 2025-01-01
    “…Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to analyze and screen variables. Predictive models were constructed by integrating key clinical features, and eight machine learning algorithms were evaluated to identify the most effective model. …”
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    Article
  20. 500

    Development and Validation of a Discrete Element Simulation Model for Pressing Holes in Sowing Substrates by Hongmei Xia, Chuheng Deng, Teng Yang, Runxin Huang, Jianhua Ou, Lingjin Dong, Dewen Tao, Long Qi

    Published 2025-04-01
    “…A neural network model for predicting the angle of repose was constructed, and a genetic algorithm was applied to optimize the significant contact mechanical parameters. …”
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    Article