Showing 1,121 - 1,140 results of 1,436 for search '((((mode OR made) OR (((model OR model) OR model) OR model)) OR model) OR more) screening algorithm', query time: 0.17s Refine Results
  1. 1121

    Association between pace of biological aging and cancer and the modulating role of physical activity: a national cross-sectional study by Jingying Nong, Yu Wang, Yi Zhang

    Published 2025-06-01
    “…Epigenetic clocks, derived from sets of DNA methylation CpGs and mathematical algorithms, have demonstrated a remarkable ability to indicate biological aging and age-related health risks. …”
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  2. 1122

    EEG Signal Analysis for Numerical Digit Classification: Methodologies and Challenges by Augoustos Tsamourgelis, Adam Adamopoulos

    Published 2025-02-01
    “…We achieve strong differentiation capabilities between digit and non-digit values in all classification algorithms. However, our study also highlights the profound neurological challenges encountered in distinguishing between the digit values, as our model, inspired by the related bibliography, was unable to differentiate between digit values 0 and 1. …”
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  3. 1123

    Implementation costs and cost-effectiveness of ultraportable chest X-ray with artificial intelligence in active case finding for tuberculosis in Nigeria. by Tushar Garg, Stephen John, Suraj Abdulkarim, Adamu D Ahmed, Beatrice Kirubi, Md Toufiq Rahman, Emperor Ubochioma, Jacob Creswell

    Published 2025-06-01
    “…We provide implementation cost and cost-effectiveness estimates of different screening algorithms using symptoms, CXR and AI in Nigeria. …”
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  4. 1124

    RNA m7G methylation regulators and targets significantly contribute to chronic obstructive pulmonary disease by Chenyu Zhu, Luyi Tan, Xinyu Zhang, Wenli Cheng, Min Li, Yibo Chen, Wenjuan Zhang

    Published 2025-03-01
    “…In this study, the combined roles of m7G methylation regulators were explored in COPD for the first time by integrated bioinformatic methods. The machine algorithms screened 7 disease signature genes relevant to clinical indicators, including CYFIP2, EIF3D, EIF4G3, GEMIN5, METTL1, SNUPN and NCBP2, and METTL1 was related to the progression in COPD. …”
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  5. 1125

    Effectiveness of mindfulness-based therapy, stress reduction in hypertension and prehypertension: a systematic review by D. I. Nozdrachev, M. N. Solovieva, K. A. Zamyatin

    Published 2022-09-01
    “…The systematic review was prepared according to the PRISMA algorithm with minor modifications. The search algorithm included articles in Russian and English, indexed in the Pubmed/MEDLINE and Cochrane Library databases. …”
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  6. 1126
  7. 1127

    The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea by Rafael Rodrigues dos Santos, Matheo Bellini Marumo, Alan Luiz Eckeli, Helio Cesar Salgado, Luiz Eduardo Virgílio Silva, Renato Tinós, Rubens Fazan

    Published 2025-03-01
    “…IntroductionObstructive sleep apnea (OSA) is a prevalent sleep disorder with a high rate of undiagnosed patients, primarily due to the complexity of its diagnosis made by polysomnography (PSG). Considering the severe comorbidities associated with OSA, especially in the cardiovascular system, the development of early screening tools for this disease is imperative. …”
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  8. 1128

    A Non-Uniformity Correction Method for Uncooled Infrared Polarization Imaging Systems by Cailing Zhao, Zhiguo Fan, Yunxiang Zhang

    Published 2025-01-01
    “…Previous non-uniformity correction (NUC) algorithms usually couple polarization information with FPN correction, resulting in the loss of polarization characteristics. …”
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  9. 1129

    Assessment of salt tolerance in peas using machine learning and multi-sensor data by Zehao Liu, Qiyan Jiang, Yishan Ji, Rong Liu, Hongquan Liu, Xiuxiu Ya, Zhenxing Liu, Zhirui Wang, Xiuliang Jin, Tao Yang

    Published 2025-09-01
    “…Recent advancements in Unmanned aerial vehicle (UAV) and sensor technologies have enabled high-throughput screening of salt-tolerant crops, offering a more efficient alternative. …”
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  10. 1130

    Comprehensive Analysis of Programmed Cell Death-Related Genes in Diagnosis and Synovitis During Osteoarthritis Development: Based on Bulk and Single-Cell RNA Sequencing Data by Zhou J, Jiao S, Huang J, Dai T, Xu Y, Xia D, Feng Z, Chen J, Li Z, Hu L, Meng Q

    Published 2025-01-01
    “…Using machine learning algorithms, Hub PCD-related differentially expressed genes (Hub PCD-DEGs) were identified. …”
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    Article
  11. 1131

    STOP-BANG: a Mandatory Tool for Targeted Respiratory Therapy in Bariatric Patients by R. D. Skvortsova, K. А. Аnisimova, K. А. Popova, V. А. Pavlova, А. N. Kulikov, D. I. Vasilevsky, S. G. Balandov, Z. А. Zaripova, А. А. Kazachenko, Yu. D. Rabik, T. S. Razumovskaya

    Published 2022-01-01
    “…Identification of patients with obstructive sleep apnea syndrome and high respiratory risk, optimization of the screening algorithm for these patients and administration of preventive non-invasive lung ventilation, makes it possible to prevent the development of perioperative complications, reduce duration of hospital stay and reduce mortality in patients undergoing surgery and bariatric surgery specifically.The objective: to evaluate the effectiveness of STOP-BANG questionnaire for preventive targeted respiratory therapy to reduce the risk of complications in bariatric patients. …”
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  12. 1132

    Weak fault diagnosis method for rolling bearings under strong background noise based on EEMD-FK-AMCKD by XIE Guizhong, XU Shuaiqiang, DU Wenliao, LUO Shuangqiang, LI Hao, WANG Liangwen, GONG Xiaoyun

    Published 2025-08-01
    “…ObjectiveTo address the challenge of accurately capturing weak features in vibration signals under strong noise interference, a joint filtering method combining ensemble empirical mode decomposition (EEMD), fast kurtogram (FK), and adaptive maximum correlation kurtosis deconvolution (AMCKD) was proposed.MethodsFirstly, the vibration signal was decomposed into multiple intrinsic mode functions (IMF) via EEMD for multiscale analysis. …”
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  13. 1133

    Evaluation of the shielding initiative in Wales (EVITE Immunity): protocol for a quasiexperimental study by Stephen Jolles, Ashley Akbari, Andrew Carson-Stevens, Helen Snooks, Alan Watkins, Adrian Edwards, Ann John, Alison Porter, Victoria Williams, Bridie Angela Evans, Ronan Lyons, Bernadette Sewell, Mark Rhys Kingston, Tony Whiffen, Jane Lyons, Rowena Bailey, Catherine A Thornton, Lesley Bethell, Samantha Bufton, Lucy Dixon

    Published 2022-09-01
    “…Clinically extremely vulnerable people identified through algorithms and screening of routine National Health Service (NHS) data were individually and strongly advised to stay at home and strictly self-isolate even from others in their household. …”
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  14. 1134

    Review of applications of deep learning in veterinary diagnostics and animal health by Sam Xiao, Navneet K. Dhand, Zhiyong Wang, Kun Hu, Kun Hu, Peter C. Thomson, John K. House, Mehar S. Khatkar, Mehar S. Khatkar

    Published 2025-03-01
    “…Deep learning (DL), a subfield of artificial intelligence (AI), involves the development of algorithms and models that simulate the problem-solving capabilities of the human mind. …”
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  15. 1135

    Research trends among new investigators at ISOQOL: a bibliometric analysis from 2019 to 2023 by Jae-Yung Kwon, Manraj N. Kaur, Ellen B. M. Elsman, Ava Mehdipour, Lori Suet Hang Lo, Ahmed M. Y. Osman, Sandrine Herbelet, Carrie-Anne Ng, Lotte van der Weijst, on behalf of the New Investigators Special Interest Group Members

    Published 2025-05-01
    “…Methodology Data on publications authored by 56 NI-SIG members between 2019 and 2023 were extracted from Web of Science and Scopus. A two-step screening process, guided by the Wilson and Cleary model of QoL, identified 561 unique documents for analysis. …”
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  16. 1136

    ATP6V0A4 as a novel prognostic biomarker and potential therapeutic target in oral squamous cell carcinoma by Xiaopu Gao, Jiamin Zhou, Yu Qiao, Chuyin Lin, Guanxiong Zhang, Qiuyu Wu, Zhikang Su, Qianji Zhang, Songkai Huang

    Published 2025-07-01
    “…Methods This study initially integrated TCGA and GEO databases for cross-platform differential gene screening. A prognostic model was constructed using univariate Cox regression and LASSO regression, complemented by random forest algorithms to identify core genes. …”
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  17. 1137

    A Combined Deep CNN: LSTM with a Random Forest Approach for Breast Cancer Diagnosis by Almas Begum, V. Dhilip Kumar, Junaid Asghar, D. Hemalatha, G. Arulkumaran

    Published 2022-01-01
    “…Computer-aided diagnosis (CAD) has minimum intervention of humans and produces more accurate results than humans. It will be a difficult and long task that depends on the expertise of pathologists. …”
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  18. 1138

    A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies by Jingyuan Zhao, Zehua Chen

    Published 2012-01-01
    “…This approach consists of a screening stage and a selection stage. In the screening stage, main-effect and interaction-effect features are screened by using L1-penalized logistic like-lihoods. …”
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  19. 1139

    Iterative phase contrast CT reconstruction with novel tomographic operator and data-driven prior. by Stefano van Gogh, Subhadip Mukherjee, Jinqiu Xu, Zhentian Wang, Michał Rawlik, Zsuzsanna Varga, Rima Alaifari, Carola-Bibiane Schönlieb, Marco Stampanoni

    Published 2022-01-01
    “…Moreover, the highly ill-conditioned differential nature of the GI-CT forward operator renders the inversion from corrupted data even more cumbersome. In this paper, we propose a novel regularized iterative reconstruction algorithm with an improved tomographic operator and a powerful data-driven regularizer to tackle this challenging inverse problem. …”
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  20. 1140

    Integrating status-neutral and targeted HIV testing in Zimbabwe: A complementary strategy. by Hamufare D Mugauri, Owen Mugurungi, Joconiah Chirenda, Kudakwashe Takarinda, Prosper Mangwiro, Mufuta Tshimanga

    Published 2025-01-01
    “…First tests were 65% more likely to test HIV positive (a95%CI: 1.43, 1.91) whilst screened patients were 3.89 times more likely to link to HIV prevention services (a95%CI: 3.05, 4.97), against 25.5% (n = 1,871) linkage among patients not screened.…”
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