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Showing 861 - 880 results of 1,273 for search '(((mode OR (model OR model)) OR model) OR made) screening algorithm', query time: 0.15s Refine Results
  1. 861

    Prediction of EGFR mutations in non-small cell lung cancer: a nomogram based on 18F-FDG PET and thin-section CT radiomics with machine learning by Jianbo Li, Qin Shi, Yi Yang, Jikui Xie, Qiang Xie, Ming Ni, Xuemei Wang, Xuemei Wang

    Published 2025-04-01
    “…After selecting optimal radiomic features, four machine learning algorithms, including logistic regression (LR), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBoost), were used to develop and validate radiomics models. …”
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    Article
  2. 862

    Exploring the role of repetitive negative thinking in the transdiagnostic context of depression and anxiety in children by Kuiliang Li, Lei Ren, Xiao Li, Chang Liu, Xuejiao Tan, Ming Ji, Xi Luo

    Published 2025-08-01
    “…Network analysis revealed that RNT’s core features exhibited the highest bridge betweenness and bridge expected influence, indicating a critical mediating role in the co-occurrence of symptoms. The random forest model showed optimal predictive performance (AUC = 0.90, recall = 0.95), supporting its applicability for early screening. …”
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  3. 863

    DEVELOPMENT OF SOFTWARE SYSTEM FOR MONITORING OF STRESS CORROSION CRACKING OF THE PIPELINE UNDER TENSION by Z. K. Abaev, B. A. Bachiev

    Published 2016-07-01
    “…The working algorithm of developed program and the screen forms are presented.…”
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  4. 864

    MYOPIA PREVALENCE AMONG STUDENTS DURING COVID-19 PANDEMIC. A SYSTEMATIC REVIEW AND META-ANALYSIS by Natasha Hana Savitri, Adinda Sandya Poernomo, Muhammad Bagus Fidiandra1, Eka Candra Setyawan1, Arinda Putri Auna Vanadia1, Bulqis Inas Sakinah1, Lilik Djuari

    Published 2022-12-01
    “…Data retrieval used the PICO method and journal adjustments were selected using the PRISMA algorithm. Data analysis was performed using a random-effects model. …”
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    Article
  5. 865

    Predictive value of dendritic cell-related genes for prognosis and immunotherapy response in lung adenocarcinoma by Zihao Sun, Mengfei Hu, Xiaoning Huang, Minghan Song, Xiujing Chen, Jiaxin Bei, Yiguang Lin, Size Chen

    Published 2025-01-01
    “…Leveraging the Coxboost and random survival forest combination algorithm, we filtered out six DC-related genes on which a prognostic prediction model, DCRGS, was established. …”
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  6. 866

    Hyperspectral estimation of chlorophyll density in winter wheat using fractional-order derivative combined with machine learning by Chenbo Yang, Chenbo Yang, Meichen Feng, Juan Bai, Hui Sun, Rutian Bi, Lifang Song, Chao Wang, Yu Zhao, Wude Yang, Lujie Xiao, Meijun Zhang, Xiaoyan Song

    Published 2025-01-01
    “…In conclusion, based on the winter wheat ChD data set and the corresponding canopy hyperspectral data set, combined with 3 FOD calculation methods, 1 band screening method, and 8 modeling algorithms, this study constructed hyperspectral monitoring models for winter wheat ChD. …”
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  7. 867

    FDTooth: Intraoral Photographs and CBCT Images for Fenestration and Dehiscence Detection by Keyuan Liu, Marawan Elbatel, Guang Chu, Zhiyi Shan, Fung Hou Kumoi Mineaki Howard Sum, Kuo Feng Hung, Chengfei Zhang, Xiaomeng Li, Yanqi Yang

    Published 2025-06-01
    “…The developed dataset and model can serve as valuable resources for research on interdisciplinary dental diagnostics, offering clinicians a non-invasive, efficient method for early FD screening without invasive procedures.…”
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    Article
  8. 868

    Few-Shot Intelligent Anti-Jamming Access with Fast Convergence: A GAN-Enhanced Deep Reinforcement Learning Approach by Tianxiao Wang, Yingtao Niu, Zhanyang Zhou

    Published 2025-08-01
    “…The method constructs a Generative Adversarial Network (GAN) to learn the time–frequency distribution characteristics of short-period jamming and to generate high-fidelity mixed samples. Furthermore, it screens qualified samples using the Pearson correlation coefficient to form a sample set, which is input into the DQN network model for pre-training to expand the experience replay buffer, effectively improving the convergence speed and decision accuracy of DQN. …”
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  9. 869

    Intratumoral and peritumoral CT radiomics in predicting anaplastic lymphoma kinase mutations and survival in patients with lung adenocarcinoma: a multicenter study by Weiyue Chen, Guihan Lin, Ye Feng, Yongjun Chen, Yanjun Li, Jianbin Li, Weibo Mao, Yang Jing, Chunli Kong, Yumin Hu, Minjiang Chen, Shuiwei Xia, Chenying Lu, Jianfei Tu, Jiansong Ji

    Published 2025-03-01
    “…The GPTV3 radiomics model using a support vector machine algorithm achieved the best predictive performance, with the highest average AUC of 0.811 in the validation sets. …”
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    Article
  10. 870

    The signature based on interleukin family and receptors identified IL19 and IL20RA in promoting nephroblastoma progression through STAT3 pathway by Chen Ding, Hongjie Gao, Liting Zhang, Zhiyi Lu, Bowen Zhang, Ding Li, Fengyin Sun

    Published 2025-04-01
    “…A prognostic model was constructed based on five selected IL(R)s using the LASSO Cox regression algorithm. …”
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    Article
  11. 871

    Adaptive Feature Selection of Unbalanced Data for Skiing Teaching by Tao Feng

    Published 2025-06-01
    “…If the features are not selected, the model may overly rely on the features of common actions and ignore the features of difficult actions. …”
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    Article
  12. 872

    Early breast cancer detection via infrared thermography using a CNN enhanced with particle swarm optimization by Riyadh M. Alzahrani, Mohamed Yacin Sikkandar, S. Sabarunisha Begum, Ahmed Farag Salem Babetat, Maryam Alhashim, Abdulrahman Alduraywish, N. B. Prakash, Eddie Y. K. Ng

    Published 2025-07-01
    “…An Enhanced Particle Swarm Optimization (EPSO) algorithm is integrated to automatically fine-tune CNN hyperparameters, thereby minimizing manual effort and enhancing computational efficiency. …”
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    Article
  13. 873

    Golden eagle optimized CONV-LSTM and non-negativity-constrained autoencoder to support spatial and temporal features in cancer drug response prediction by Wesam Ibrahim Hajim, Suhaila Zainudin, Kauthar Mohd Daud, Khattab Alheeti

    Published 2024-12-01
    “…Advanced machine learning (ML) and deep learning (DL) methods have recently been utilized in Drug Response Prediction (DRP), and these models use the details from genomic profiles, such as extensive drug screening data and cell line data, to predict the response of drugs. …”
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  14. 874

    Automated interpretation of influenza hemagglutination inhibition (HAI) assays: Is plate tilting necessary? by Garrett Wilson, Zhiping Ye, Hang Xie, Steven Vahl, Erica Dawson, Kathy Rowlen

    Published 2017-01-01
    “…In a side-by-side comparison study performed during FDA's biannual serological screening process for influenza viruses, titer calls for more than 2200 serum samples were made by the Cypher One automated hemagglutination analyzer without tilting and by an expert human with tilting. …”
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  15. 875

    An integrated bioinformatic investigation of succinic acid metabolism related genes in ccRCC followed by preliminary validation of SLC25A4 in tumorigenesis by Dong Yue, Fengyun Dong, Sen Wang, Miao Zheng

    Published 2025-06-01
    “…The univariate Cox algorithm, LASSO, and multivariate Cox analysis were performed to obtain biomarkers and build a prognostic model. …”
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    Article
  16. 876

    Leveraging automated time-lapse microscopy coupled with deep learning to automate colony forming assay by Anusha Klett, Anusha Klett, Dennis Raith, Dennis Raith, Paula Silvestrini, Paula Silvestrini, Paula Silvestrini, Matías Stingl, Jonas Bermeitinger, Avani Sapre, Avani Sapre, Avani Sapre, Martin Condor, Roman Melachrinos, Mira Kusterer, Alexandra Brand, Guido Pisani, Guido Pisani, Evelyn Ullrich, Evelyn Ullrich, Evelyn Ullrich, Evelyn Ullrich, Marie Follo, Marie Follo, Jesús Duque-Afonso, Roland Mertelsmann, Roland Mertelsmann

    Published 2025-02-01
    “…Brightfield images were used to train a YOLOv8 object detection network, achieving a mAP50 score of 86% for identifying single cells, clusters, and colonies, and 97% accuracy for Z-stack colony identification with a multi-object tracking algorithm. The detection model accurately identified the majority of objects in the dataset.ResultsThis AI-assisted CFA was successfully applied for density optimization, enabling the determination of seeding densities that maximize plating efficiency (PE), and for IC50 determination, offering an efficient, less labor-intensive method for testing drug concentrations. …”
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  17. 877

    Acoustic-based machine learning approaches for depression detection in Chinese university students by Yange Wei, Yange Wei, Shisen Qin, Fengyi Liu, Rongxun Liu, Yunze Zhou, Yuanle Chen, Xingliang Xiong, Wei Zheng, Guangjun Ji, Yong Meng, Fei Wang, Fei Wang, Ruiling Zhang

    Published 2025-05-01
    “…Among five machine learning algorithms, LDA model demonstrated the highest classification performance, with an AUC of 0.771. …”
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    Article
  18. 878

    Leveraging diverse cell-death patterns in diagnosis of sepsis by integrating bioinformatics and machine learning by Mi Liu, Xingxing Gao, Hongfa Wang, Yiping Zhang, Xiaojun Li, Renlai Zhu, Yunru Sheng

    Published 2025-02-01
    “…The machine learning algorithm screened three PCD-related genes, NLRC4, TXN and S100A9, as potential biomarkers for sepsis. …”
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    Article
  19. 879

    A machine learning framework for predicting cognitive impairment in aging populations using urinary metal and demographic data by Fengchun Ren, Xiao Zhao, Qin Yang, Huaqiang Liao, Yudong Zhang, Xuemei Liu

    Published 2025-06-01
    “…Ultimately, a user-friendly webserver was deployed for the predictive model and is freely accessed at http://bio-medical.online/admxp/.DiscussionThe associated webserver enables accessible risk screening and underpins precision prevention strategies in aging populations.…”
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    Article
  20. 880

    Empowering Healthcare: TinyML for Precise Lung Disease Classification by Youssef Abadade, Nabil Benamar, Miloud Bagaa, Habiba Chaoui

    Published 2024-10-01
    “…These findings highlight the potential of TinyML to provide accessible, reliable, and real-time diagnostic tools, particularly in remote and underserved areas, demonstrating the transformative impact of integrating advanced AI algorithms into portable medical devices. This advancement facilitates the prospect of automated respiratory health screening using lung sounds.…”
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    Article