Showing 19,021 - 19,040 results of 23,214 for search '"Prediction', query time: 0.14s Refine Results
  1. 19021

    Prognostic signature and therapeutic drug identification for dilated cardiomyopathy based on necroptosis via bioinformatics and experimental validation by Han Yang, Zhenwei Wang, Yawei Xu, Yimei Du, Haibo Yang, Yang Lu

    Published 2025-01-01
    “…We identified five necroptosis-related genes (BID, CAMK2B, GLUL, HSP90AB1, CHMP5) that define a necroptosis-related signature with strong predictive value, evidenced by ROC curve areas of 0.852 and 0.957 in training and test sets, respectively. …”
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  2. 19022

    Mental health and socio-cognitive predictors of adherence to COVID-19 social distancing rules in adolescents in England by Giacomo Bignardi, Saz P. Ahmed, Marc Bennett, Darren Dunning, Kirsty Griffiths, Jovita T. Leung, Ashok Sakhardande, Blanca Piera Pi-Sunyer, Willem Kuyken, Tim Dalgleish, Sarah-Jayne Blakemore

    Published 2025-01-01
    “…Bayesian ordinal regression models were used to predict adherence to social distancing from predictors, controlling for age at pandemic, gender, day of assessment, and intervention group. …”
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  3. 19023

    Integrating novel stellarator single-stage optimization algorithms to design the Columbia stellarator experiment by A. Baillod, E.J. Paul, G. Rawlinson, M. Haque, S.W. Freiberger, S. Thapa

    Published 2025-01-01
    “…The Columbia Stellarator eXperiment (CSX), currently being designed at Columbia University, aims to test theoretical predictions related to QA plasma behavior, and to pioneer the construction of an optimized stellarator using three-dimensional, non-insulated high-temperature superconducting (NI-HTS) coils. …”
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  4. 19024

    Investigating crack growth in two-dimensional plates with openings using the peri-dynamic method by Mohammad Norouzi Shavir, Pouria Biglari, Navid Mirzaii, Reza Rashmehkarim, Peyman Beiranvand

    Published 2024-09-01
    “…The comparison of different results showed that the peri-dynamics method is capable of properly modeling crack growth in plates and shells with openings, and in other words, this theory can predict the path of crack growth with high accuracy. …”
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  5. 19025

    Correlation between Fine-Needle Aspiration Cytology and Histology for Palpable Breast Masses in a Nigerian Tertiary Health Institution by Adetola Olubunmi Daramola, Mosebolatan Olatokunboh Odubanjo, Fred John Obiajulu, Nzechukwu Zimudo Ikeri, Adekunbiola Aina Fehintola Banjo

    Published 2015-01-01
    “…Our results compare favourably with the measures of test performance of the UK NHS Breast Screening Programme shown in brackets: absolute sensitivity 95.4% (>70%), complete sensitivity 99.2% (>90%), full specificity 88.9% (>65%), positive predictive value 99.6% (>99%), false-negative rate 0.8% (<4%), false-positive rate 0.4% (<0.5%), inadequate rate 3.2% (<15%), and suspicious rate 10.2% (<15%). …”
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  6. 19026

    Elevated Serum Ceruloplasmin Levels Are Associated with Higher Impulsivity in People with Parkinson’s Disease by Megan C. Bakeberg, Maddeson Riley, Michelle Byrnes, Alexa Jefferson, Souyma Ghosh, Malcom K. Horne, Sarah McGregor, Rick Stell, Sue Walters, Tess Evans, Katherine Roberts, Frank L. Mastaglia, Ryan S. Anderton

    Published 2020-01-01
    “…Multivariate general linear models (GLMs) were used to identify whether higher serum ceruloplasmin levels (>75th percentile) were significantly predictive of BIS-11 scores. Results. Serum ceruloplasmin was higher in females with PD (p<0.001) and associated with MDS-UPDRS III, Hoehn and Yahr, and ACE-R scores (p<0.05). …”
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  7. 19027

    Comparing Supervised Machine Learning Models for Covid-19 patient detection using a Combination of Clinical and Laboratory Dataset by Narges Mohebbi, Mehdi Tutunchian, Meysam Alavi, Mehrdad Kargari, Amir Behnam Kharazmy

    Published 2022-01-01
    “…The results of this research indicate that based on the evaluation criteria, XGBoost and K-NN models have the most accuracy among the mentioned models and can be considered suitable predictive models for the diagnosis of COVID-19.…”
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  8. 19028

    Synthesis of dendritic silver nano powder using pulsing electrolysis in ammonia solution by Soltanzadeh A., Shahini S., Rashchi F., Saba M.

    Published 2019-01-01
    “…A mathematical model was also presented. The predicted silver nano size dendrite arm at the optimum condition was found to be 87.29 nm which was very close to the experimental value of 90 nm.…”
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  9. 19029
  10. 19030

    The radial spreading of volcanic umbrella clouds deduced from satellite measurements by Fred Prata, Andrew T. Prata, Rebecca Tanner, Roy G. Grainger, Michael Borgas, Thomas J. Aubry

    Published 2025-01-01
    “…A hyperbolic tangent model, r ~ tanh(t) is presented that matches the entire radial spreading time history and has a conserved torus-shaped volume in which the intrusion depth is proportional to sech(t). This model also predicts the observed radial velocities. The data and the model estimates of the volumetric flow rate for the 15 January 2022 Hunga eruption are found to be 3.6–5 × 1011 m3s−1, the largest ever measured.…”
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  11. 19031

    Clinical Evaluation of Subcutaneous Lactate Measurement in Patients after Major Cardiac Surgery by Martin Ellmerer, Martin Haluzik, Jan Blaha, Jaromir Kremen, Stepan Svacina, Andreas Plasnik, Dimas Ikeoka, Manfred Bodenlenz, Lukas Schaupp, Johannes Plank, Thomas R. Pieber

    Published 2009-01-01
    “…In conclusion, replacement of arterial blood lactate measurements by readings from SAT is associated with a substantial shortcoming in clinical predictability in patients after major cardiac surgery.…”
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  12. 19032

    Elastography Evaluation of Benign Thyroid Nodules in Patients Affected by Hashimoto’s Thyroiditis by Carlo Cappelli, Ilenia Pirola, Elena Gandossi, Annamaria Formenti, Barbara Agosti, Maurizio Castellano

    Published 2015-01-01
    “…The aim of the present prospective study was to evaluate the predictive value of elastography in benign thyroid nodules of patients affected by Hashimoto’s thyroiditis (HT). …”
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  13. 19033

    Vaccine hesitancy or hesitancies? A latent class analysis of pediatric patients' parents by Don E. Willis, Marie‐Rachelle Narcisse, Laura James, James P. Selig, Mohammed Ason, Aaron J. Scott, Lawrence E. Cornett, Pearl A. McElfish

    Published 2025-01-01
    “…Which sociodemographic, health access, and health‐related variables are predictive of membership in those classes? To answer those questions, we analyze online survey data from parents of pediatric patients recruited through eight clinics within the University of Arkansas for Medical Sciences Rural Research Network. …”
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  14. 19034

    Bio-Waste in Reverse Logistics - Various Size Cities on the Example of South-Eastern Poland by KOC-JURCZYK Justyna, JURCZYK Łukasz, PODOLAK Agnieszka

    Published 2025-01-01
    “…Discrepancies were found between the collected mass of bio-waste and its predicted mass, which may be due to several reasons. …”
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  15. 19035

    Massively parallel homogeneous amplification of chip-scale DNA for DNA information storage (MPHAC-DIS) by Zhi Weng, Jiangxue Li, Yi Wu, Xuehao Xiu, Fei Wang, Xiaolei Zuo, Ping Song, Chunhai Fan

    Published 2025-01-01
    “…The programmable and predictable MPHAC-DIS method thus opens new door for DNA-based large-scale data storage with potential industrial applications.…”
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  16. 19036
  17. 19037
  18. 19038

    Prognostic value of the pretreatment Naples prognostic score in patients with colorectal cancer: a systematic review and meta-analysis by Hui Liu, Dailiang Zhu, Dequan Jiang, Huayang Pang, Xiaolian Yang

    Published 2025-01-01
    “…Furthermore, sensitivity analyses confirmed the robustness of these combined results.ConclusionThe pretreatment NPS could serve as a valuable biomarker for predicting long-term oncological outcomes in patients diagnosed with colorectal cancer.…”
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  19. 19039
  20. 19040

    A Correlation Analysis-Based Structural Load Estimation Method for RC Beams Using Machine Vision and Numerical Simulation by Chun Zhang, Yinjie Zhao, Guangyu Wu, Han Wu, Hongli Ding, Jian Yu, Ruoqing Wan

    Published 2025-01-01
    “…Subsequently, a deep neural network (DNN) is trained as a FEM surrogate model to quickly predict the structural strain response by considering material uncertainties. …”
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