Showing 1,101 - 1,120 results of 1,436 for search '((((mode OR ((model OR made) OR made)) OR made) OR made) OR more) screening algorithm', query time: 0.19s Refine Results
  1. 1101

    Integrated single-cell and transcriptome sequencing data reveal the value of IL1RAP in gastric cancer microenvironment and prognosis by Weifeng Yang, Xiaohua Wu, Jian Wang, Wenquan Ou, Xing Huang

    Published 2025-05-01
    “…Immunotherapy prediction models suggested a more favorable response to PD-1 treatment in the low IL1RAP expression group. …”
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    Article
  2. 1102

    Plasma metabolite biomarker identification study for the early detection of gastric cancer by Juan Zhu, Yida Huang, Bin Liu, Xue Li, Li Yuan, Le Wang, Kun Qian, Yingying Mao, Lingbin Du, Xiangdong Cheng

    Published 2025-02-01
    “…Ultra-performance liquid chromatography–mass spectrometry–based metabolomics methods were used to characterize the subjects’ plasma metabolic profiles and to screen and validate the GC biomarkers. Five machine learning algorithms (neural network, support vector machine, ridge regression, lasso regression and Naïve Bayes) were used to build a diagnostic model. …”
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    Article
  3. 1103

    Biomarker-driven drug repurposing for NAFLD-associated hepatocellular carcinoma using machine learning integrated ensemble feature selection by Subhajit Ghosh, Sukhen Das Mandal, Subarna Thakur

    Published 2025-04-01
    “…The incidence of non-alcoholic fatty liver disease (NAFLD), encompassing the more severe non-alcoholic steatohepatitis (NASH), is rising alongside the surges in diabetes and obesity. …”
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  4. 1104

    Distinguish the Value of the Benign Nevus and Melanomas Using Machine Learning: A Meta-Analysis and Systematic Review by Suli Li, Yihang Chu, Ying Wang, Yantong Wang, Shipeng Hu, Xiangye Wu, Xinwei Qi

    Published 2022-01-01
    “…This suggests that state-of-the-art ML-based algorithms for distinguishing melanoma from benign nevi may be ready for clinical use. …”
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    Article
  5. 1105

    Optimized Allocation of Flood Control Emergency Materials Based on Loss Quantification by Wei Wang, Yunqing Wang, Li Huang, Yue Song

    Published 2025-06-01
    “…The center of gravity method is used to address demand when constructing the quantitative function of out‐of‐stock loss. The NSGA‐II algorithm was selected to generate the results after the method comparison to ultimately determine the Pareto solution of the model. …”
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    Article
  6. 1106

    Peripherex Home Visual Field Demonstrates High Test-Retest Reliability, Validity by Schweitzer J, Ibach M, Berdahl J, Daoud M, Daoud YA, Kempinski Y, Goldberg JL

    Published 2025-06-01
    “…These data support in-home use of the PRX VFT by the eye care provider for screening and monitoring in glaucoma, and may be extended to the screening and monitoring of other retinal, optic nerve and neurological diseases.Keywords: visual field test, glaucoma, home healthcare, prospective clinical trial…”
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  7. 1107

    Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning by Sijia Liu, Jiawei Luo, Chengqi He

    Published 2025-05-01
    “…Then, based on the key features screened out, a dynamic treatment recommendation system was constructed by using deep reinforcement learning algorithms, including Deep Deterministic Policy Gradien(DDPG), Deep Q-Network(DQN) and Batch-Constrained Q-learning(BCQ). …”
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  8. 1108

    Role of arachidonic acid metabolism in osteosarcoma prognosis by integrating WGCNA and bioinformatics analysis by Yaling Wang, Peichun HSU, Haiyan Hu, Feng Lin, Xiaokang Wei

    Published 2025-03-01
    “…An AA metabolism predictive model of the five AAMRGs were established by Cox regression and the LASSO algorithm. …”
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  9. 1109

    Prospective Validation and Usability Evaluation of a Mobile Diagnostic App for Obstructive Sleep Apnea by Pedro Amorim, Daniela Ferreira-Santos, Marta Drummond, Pedro Pereira Rodrigues

    Published 2024-11-01
    “…Current guidelines recommend the development of clinical prediction algorithms in screening prior to PSG. A recent intuitive and user-friendly tool (OSABayes), based on a Bayesian network model using six clinical variables, has been proposed to quantify the probability of OSA. …”
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  10. 1110

    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. 1111

    CNN-Based Medical Ultrasound Image Quality Assessment by Siyuan Zhang, Yifan Wang, Jiayao Jiang, Jingxian Dong, Weiwei Yi, Wenguang Hou

    Published 2021-01-01
    “…At last, some tests are taken to evaluate the IQA models. They show that the CNN-based IQA is feasible and effective.…”
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  12. 1112

    Advances in the application of machine learning technology in the field of environmental health by ZHENG Yu, LI Cheng, HU Guiping, JIA Guang

    Published 2024-11-01
    “…However, the application of ML technology in the field of environmental health still faces challenges such as data quality, model interpretability, and interdisciplinary cooperation. …”
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    Article
  13. 1113

    Prevalence associations of various risk factors and arterial hypertension in male open urban population (by a one stage epidemiological study) by Е. V. Akimova, M. Yu. Akimov, E. I. Gakova, M. М. Kayumova, V. V. Gafarov, V. A. Kuznetsova

    Published 2018-09-01
    “…For the analysis of AH the data from cardiological screening was used, and surveying by psychosocial methods in algorithms of MONICA-MOPSY.Results. …”
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  14. 1114
  15. 1115
  16. 1116

    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
  17. 1117

    Detectability of Liver Steatosis and Fibrosis with Transient Elastography and Controlled Attenuation Parameter in Residents of St. Petersburg by V. P. Kovyazina, K. L. Raikhelson, M. K. Prashnova, E. V. Pazenko, L. K. Palgova, E. A. Kondrashina

    Published 2021-04-01
    “…Petersburg warrants improved diagnostic algorithms and routine preventive measures. Transient elastography with the controlled attenuation parameter estimation provides a convenient non-invasive screening for hepatic fibrosis and steatosis.…”
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  18. 1118

    Identification of novel cyclin-dependent kinase 4/6 inhibitors from marine natural products. by Abhijit Debnath, Rupa Mazumder, Anil Kumar Singh, Rajesh Kumar Singh

    Published 2025-01-01
    “…These 25 candidates underwent consensus molecular docking using seven distinct algorithms: AutoDockTools 4.2, idock, LeDock, Qvina 2, Smina, AutoDock Vina 1.2.0, PLANTS, and rDock. …”
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  19. 1119

    The Clinical Significance of the Dense Fine Speckled Immunofluorescence Pattern on HEp-2 Cells for the Diagnosis of Systemic Autoimmune Diseases by Michael Mahler, Marvin J. Fritzler

    Published 2012-01-01
    “…The indirect immunofluorescence (IIF) assay on HEp-2 cells is a commonly used test for the detection of ANA and has been recently recommended as the screening test of choice by a task force of the American College of Rheumatology. …”
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  20. 1120

    Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis by Hamed Hajishah, Danial Kazemi, Ehsan Safaee, Mohammad Javad Amini, Maral Peisepar, Mohammad Mahdi Tanhapour, Arian Tavasol

    Published 2025-04-01
    “…In total, 346 machine learning models were evaluated, with the most common algorithms being random forest, logistic regression, and gradient boosting. …”
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    Article