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Showing 441 - 460 results of 1,414 for search '((((mode OR model) OR model) OR model) OR more) screening algorithm', query time: 0.23s Refine Results
  1. 441
  2. 442

    Recent Applications of In Silico Approaches for Studying Receptor Mutations Associated with Human Pathologies by Matteo Pappalardo, Federica Maria Sipala, Milena Cristina Nicolosi, Salvatore Guccione, Simone Ronsisvalle

    Published 2024-11-01
    “…The reported techniques include virtual screening, homology modeling, threading, docking, and molecular dynamics. …”
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    Article
  3. 443

    Artificial Intelligence–Enabled ECG Screening for LVSD in LBBB by Hak Seung Lee, MD, Sooyeon Lee, MD, Sora Kang, MS, Ga In Han, MS, Ah-Hyun Yoo, MS, Jong-Hwan Jang, PhD, Yong-Yeon Jo, PhD, Jeong Min Son, MD, Min Sung Lee, MD, MS, Joon-myoung Kwon, MD, MS, Kyung-Hee Kim, MD, PhD

    Published 2025-09-01
    “…Although artificial intelligence (AI)–driven ECG analysis shows promise for LVSD screening, it remains unclear if a general AI-ECG model or one tailored for LBBB patients yields better performance. …”
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    Article
  4. 444

    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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    Article
  5. 445

    Kriging-Based Variable Screening Method for Aircraft Optimization Problems with Expensive Functions by Yadong Wang, Xinyao Duan, Jiang Wang, Jin Guo, Minglei Han

    Published 2025-06-01
    “…A genetic algorithm (GA) is employed to achieve the global optimum of the log-likelihood function. …”
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    Article
  6. 446

    Comprehensive quality assessment of 296 sweetpotato core germplasm in China: A quantitative and qualitative analysis by Chaochen Tang, Yi Xu, Rong Zhang, Xueying Mo, Bingzhi Jiang, Zhangying Wang

    Published 2024-12-01
    “…Near-infrared spectroscopy, combined with a random forest algorithm, enabled rapid screening of superior germplasm, achieving prediction accuracies of 97 % for stem tips and 98 % for roots. …”
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    Article
  7. 447

    Preventing Stillbirth: A Review of Screening and Prevention Strategies by Laure Noël, Conrado Milani Coutinho, Basky Thilaganathan, Yiyuan Jiang, Dandan Shi

    Published 2022-07-01
    “…More recently, the first-trimester combined screening algorithm developed by the Fetal Medicine Foundation has emerged as a better tool to predict and prevent early-onset placental dysfunction and its main outcomes of preterm preeclampsia, fetal growth restriction and stillbirth by the appropriate use of Aspirin therapy, serial growth scans and induction of labour from 40 weeks for women identified at high-risk by such screening. …”
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  8. 448

    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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  9. 449

    New Perspectives on Lung Cancer Screening and Artificial Intelligence by Leonardo Duranti, Luca Tavecchio, Luigi Rolli, Piergiorgio Solli

    Published 2025-03-01
    “…Integrating AI and biomarker-driven methods offers significant promise for transforming lung cancer screening. These technologies could enable earlier, more accurate detection, ultimately improving survival outcomes. …”
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    Article
  10. 450

    SCREENING FOR OVARIAN CANCER: REALITY AND PROSPECTS. REVIEW OF THE LITERATURE by E. V. Gerfanova, L. A. Ashrafyan, I. B. Antonova, O. I. Aleshikova, S. V. Ivashina

    Published 2015-04-01
    “…A review article presents the modern methods of screening and early diagnosis of primary ovarian cancer (OC). …”
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    Article
  11. 451

    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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  12. 452
  13. 453

    Research on Bearing Fault Diagnosis Method Based on MESO-TCN by Ruibin Gao, Jing Zhu, Yifan Wu, Kaiwen Xiao, Yang Shen

    Published 2025-06-01
    “…The method integrates feature filtering, network modeling, and parameter optimization into a unified diagnostic framework. …”
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    Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

    Published 2025-06-01
    “…The review highlights the utility of various ML approaches in classifying activity levels and significantly improving the prediction of sedentary behavior, offering a promising approach to address this widespread health issue.ConclusionML algorithms, including supervised and unsupervised models, show great potential in accurately detecting and predicting sedentary behavior. …”
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  18. 458

    An Emotion-Driven Vocal Biomarker-Based PTSD Screening Tool by Thomas F. Quatieri, Jing Wang, James R. Williamson, Richard DeLaura, Tanya Talkar, Nancy P. Solomon, Stefanie E. Kuchinsky, Megan Eitel, Tracey Brickell, Sara Lippa, Kristin J. Heaton, Douglas S. Brungart, Louis French, Rael Lange, Jeffrey Palmer, Hayley Reynolds

    Published 2024-01-01
    “…<italic>Results:</italic> Speech from low-arousal and positive-valence regions provide the highest discrimination for PTSD. Our model achieved an AUC (area under the curve) of 0.80 in detecting PCL-C ratings, outperforming models with no emotion filtering (AUC &#x003D; 0.68). …”
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