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Showing 581 - 600 results of 1,273 for search '(((mode OR model) OR model) OR made) screening algorithm', query time: 0.26s Refine Results
  1. 581

    Economic evaluation of a novel genetic screening test for risk of venous thromboembolism compared with standard of care in women considering combined hormonal contraception in Swit... by Zanfina Ademi, C Simone Sutherland, Matthias Schwenkglenks, Nadine Schur, Joëlle Michaud, Myriam Lingg, Arjun Bhadhuri, Thierry D. Pache, Johannes Bitzer, Pierre Suchon, Valerie Albert, Kurt E. Hersberger, Goranka Tanackovic

    Published 2019-11-01
    “…The risk of having a VTE was derived from the risk algorithm that underpins the PP test. The remaining model inputs relating to population characteristics, costs, health resource use, mortality and utilities were derived from published studies or national sources. …”
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    Article
  2. 582
  3. 583
  4. 584

    Driver injury severity in two-vehicle accidents considering collision role by JIN Wenzhou, PEI Xiaohang, TANG Zuogan, YAO Yinjie

    Published 2022-03-01
    “…In order to study the influencing factors of driver injury severity and the interaction effects of collision roles in two-vehicle accidents, based on the data of two-vehicle collision accidents in Shenzhen from 2018 to 2020, we calculate the value of importance degree of characteristic variables by using random forest algorithm to screen out the candidate independent variables, and establish a binary logit model of driver injury severity considering collision angle. …”
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  5. 585
  6. 586

    Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method by Kai Zhao, Haiqing Tian, Jue Zhang, Yang Yu, Lina Guo, Jianying Sun, Haijun Li

    Published 2025-01-01
    “…Extended color components, a novel sensitive dye screening method, and a feature screening method were integrated and applied to enhance pH detection. …”
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    Article
  7. 587

    Analytical screening of polymorphic variants of 20S proteasome genes when planning a study of pathogenetic effects of modification of NFKB1 post-translational processing by A. V. Meyer, M. V. Ulyanova, D. O. Imekina, A. D. Padyukova, T. A. Tolochko, E. A. Astafieva, M. B. Lavryashina

    Published 2023-06-01
    “…To calculate the genetic distances between populations, we used the methord of comparing the populations by frequencies of polymorphic marker alleles proposed by Ney, the obtained matrices are illustrated by the method of multidimensional scaling in space using Statistica v.8.0.Results. Discussion of the algorithm and results of analytical screening of polymorphic variants of 14 genes (PSMA1-PSMA7, PSMB1–PSMB7) encoding proteasome subunits 20S. …”
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  8. 588

    Estimation of Canopy Water Content by Integrating Hyperspectral and Thermal Imagery in Winter Wheat Fields by Chenkai Gao, Shuimiao Liu, Pengnian Wu, Yanli Wang, Ke Wu, Lingyun Li, Jinghui Wang, Shilong Liu, Peimeng Gao, Zhiheng Zhao, Jing Shao, Haolin Yu, Xiaokang Guan, Tongchao Wang, Pengfei Wen

    Published 2024-11-01
    “…</b> Ultimately, the CWC prediction model of winter wheat hyperspectral characteristic bands and thermal imaging information fusion was created using the GRA algorithm. …”
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  9. 589
  10. 590

    Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization by Dawen Wu, Yanfei Li, Zeyi Yang, Teng Yin, Xiaohang Chen, Jingyu Liu, Wenyi Shang, Bin Xie, Guoyuan Yang, Haixian Zhang, Longqian Liu

    Published 2025-07-01
    “…The control experiment reduced image preparation time from 10 hours for manual cropping of 900 photos to 30 seconds with the automated model. Downstream strabismus screening task validation showed our model (with head tilt correction) achieving an area under the curve of 0.917 (95% CI 0.901‐0.933), surpassing Dlib-toolkit and faster R-CNN (both without head tilt correction) with an area under the curve of 0.856 (PP ConclusionsThis study delivers an AI-driven platform featuring a preprocessing algorithm that automates eye region cropping, correcting head tilt variations to improve image quality for AI development and clinical use. …”
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  11. 591

    Recent advances in AI-based toxicity prediction for drug discovery by Hyundo Lee, Jisan Kim, Ji-Woon Kim, Yoonji Lee, Yoonji Lee

    Published 2025-07-01
    “…The advent of computational approaches has accelerated a shift toward in silico modeling, virtual screening, and, notably, artificial intelligence (AI) to identify potential toxicities earlier in the pipeline. …”
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    Article
  12. 592

    Comparison between logistic regression and machine learning algorithms on prediction of noise-induced hearing loss and investigation of SNP loci by Jie Lu, Xinhao Lu, Yixiao Wang, Hengdong Zhang, Lei Han, Baoli Zhu, Boshen Wang

    Published 2025-05-01
    “…The SNP loci screened by these models are pivotal in the process of NIHL prediction, which further improves the prediction accuracy of the model. …”
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    Article
  13. 593

    Rapid and Non-destructive Detection of Rice Protein Content Based on Near Infrared Spectroscopy by Siping TAN, Jicheng YUE, Ying CHEN, Cuihong HUANG, Danhua ZHOU, Huijuan ZHANG, Guili YANG, Hui WANG

    Published 2024-10-01
    “…Based on near infrared spectroscopy (NIRS), four pretreatment methods were used: first-order smooth derivative (SG1), second-order smooth derivative (SG2), standard normal variable (SNV) and detrend algorithm (Detrend). The near infrared detection model of rice protein contents in rice, brown rice and milled rice were established by using partial least square (PLS) method.…”
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  14. 594

    Rapid diagnosis of latent and active pulmonary tuberculosis by autofluorescence spectroscopy of blood plasma combined with artificial neural network algorithm by Fengjiao Yue, Si Li, Lijuan Wu, Xuerong Chen, Jianhua Zhu

    Published 2024-12-01
    “…This study demonstrates the possibility of using blood plasma autofluorescence spectroscopy and Artificial Neural Network (ANN) algorithm for the rapid and accurate diagnosis of latent and active pulmonary TB from healthy subjects. …”
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    Article
  15. 595

    Machine Learning-Based Prediction of First Trimester Down Syndrome Risk in East Asian Populations by Chen YT, Chen GJ, Lin YS

    Published 2025-03-01
    “…Fourteen features (including maternal age, nuchal translucency thickness, serum markers, etc.) were input into the twelve machine learning models, along with seven data-balancing algorithms, to explore the risk prediction outcomes. …”
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  16. 596

    Predicting Geostationary 40–150 keV Electron Flux Using ARMAX (an Autoregressive Moving Average Transfer Function), RNN (a Recurrent Neural Network), and Logistic Regression: A Com... by L. E. Simms, N. Yu. Ganushkina, M. Van derKamp, M. Balikhin, M. W. Liemohn

    Published 2023-05-01
    “…Abstract We screen several algorithms for their ability to produce good predictive models of hourly 40–150 keV electron flux at geostationary orbit (data from GOES‐13) using solar wind, Interplanetary Magnetic Field, and geomagnetic index parameters that would be available for real time forecasting. …”
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  17. 597

    Estimation of Daylily Leaf Area Index by Synergy Multispectral and Radar Remote-Sensing Data Based on Machine-Learning Algorithm by Minhuan Hu, Jingshu Wang, Peng Yang, Ping Li, Peng He, Rutian Bi

    Published 2025-02-01
    “…Because of low estimation accuracy of empirical models based on single-source data, we proposed a machine-learning algorithm combining optical and microwave remote-sensing data as well as the random forest regression (RFR) importance score to select features. …”
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  18. 598

    Throw out an oligopeptide to catch a protein: Deep learning and natural language processing-screened tripeptide PSP promotes Osteolectin-mediated vascularized bone regeneration by Yu Chen, Long Chen, Jinyang Wu, Xiaofeng Xu, Chengshuai Yang, Yong Zhang, Xinrong Chen, Kaili Lin, Shilei Zhang

    Published 2025-04-01
    “…In summary, our study established a precise and efficient composite model of DL and NLP to screen bioactive peptides, opening an avenue for the development of various peptide-based therapeutic strategies applicable to a broader range of diseases.…”
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  19. 599
  20. 600

    Characterization and feature selection of volatile metabolites in Yangxian pigmented rice varieties through GC-MS and machine learning algorithms by Kaiqi Cheng, Ruonan Dong, Fei Pan, Wen Su, Lingjie Xi, Meng Zhang, Jingzhang Geng, Ruichang Gao, Ruichang Gao, Wengang Jin, A. M. Abd El-Aty, A. M. Abd El-Aty

    Published 2025-05-01
    “…Four machine learning models were further used for the classification of various colored rice varieties, and random forest model was the optimum for predicting classification, with an accuracy of 0.97. …”
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    Article