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  1. 36841
    “…Differentially expressed genes were verified and screened by random forest and cox regression analysis by comparing different m(6)A modification patterns. …”
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    m(6)A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC)
  2. 36842
    “…There machine learning methods (LASSO logistic regression, random forest (RF), support vector machine-recursive feature elimination (SVM-RFE)) were used to screen out important genes. …”
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    Comprehensive molecular analyses of an autoimmune-related gene predictive model and immune infiltrations using machine learning methods in moyamoya disease
  3. 36843
    “…Descriptive statistics, univariate analyses and multivariate analyses were used. Forest plot and nomograms were constructed for the visualization of predictive results. …”
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    Relationship between occupational noise exposure and hypertension: Cross-sectional evidence from real-world
  4. 36844
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    Adjuvant chemotherapy for completely resected IIA–IIIA non-small cell lung cancer: compliance to guidelines, safety and efficacy in real-life practice
  5. 36845
    “…Performance of five algorithms were compared across the four subsets: Naïve Bayes, Logistic Regression, Support Vector Machine (SVM), Multi-Layer Perceptron (MLP) and Random Forests. Feature (input variables) selection and ten-fold cross validation was performed on all the datasets. …”
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    Identifying oral disease variables associated with pneumonia emergence by application of machine learning to integrated medical and dental big data to inform eHealth approaches
  6. 36846
    “…The resistances of the different land types and landscape heterogeneity to the ecological function of species migration between the core protected areas of the heritage site were, in descending order, those of the forest, shrubs and grass, water, unused land, cultivated land, and built-up land. …”
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    The Delineation and Ecological Connectivity of the Three Parallel Rivers Natural World Heritage Site
  7. 36847
    “…However, it is unclear whether CXCR4 and FAP positivity mark distinct microenvironments, especially in solid tumors. (2) Methods: Using Random Forest (RF) analysis, we searched for entity-independent mRNA and microRNA signatures related to CXCR4 and FAP overexpression in our pan-cancer cohort from The Cancer Genome Atlas (TCGA) database—representing n = 9242 specimens from 29 tumor entities. …”
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    Predicting Microenvironment in CXCR4- and FAP-Positive Solid Tumors—A Pan-Cancer Machine Learning Workflow for Theranostic Target Structures
  8. 36848
    por Tang, Jun, Fang, Yu, Xu, Zhe
    Publicado 2023
    “…Backpropagation artificial neural network (BP-ANN), random forest (RF), support vector machine (SVM), and naive Bayes classifier (NBC) were chosen as alternative algorithms. …”
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    Establishment of prognostic models of adrenocortical carcinoma using machine learning and big data
  9. 36849
    “…Next, Bagging, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) were employed for classification of ACR outcomes and MCR outcomes, respectively. …”
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    Machine learning-based warning model for chronic kidney disease in individuals over 40 years old in underprivileged areas, Shanxi Province
  10. 36850
    por Bian, Rutao, Xu, Xuegong, Li, Weiyu
    Publicado 2023
    “…Also, four algorithms, namely, random forest (RF), Boruta algorithm, logical regression of the selection operator (LASSO), and support vector machine-recursive feature elimination (SVM-RFE), were used to identify the candidate genes. …”
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    Uncovering the molecular mechanisms between heart failure and end-stage renal disease via a bioinformatics study
  11. 36851
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    Development and validation of the modified index of fragility in head and neck cancer surgery
  12. 36852
    “…All data was divided into the training set (n = 1,465) and the testing set (n = 628). The random survival forest model was constructed in the training set and validated in the testing set. …”
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    A prediction model for the 5-year, 10-year and 20-year mortality of medullary thyroid carcinoma patients based on lymph node ratio and other predictors
  13. 36853
    “…Four classification models were assessed for waxy cassava genotype identification: k-nearest neighbor algorithm (KNN), C5.0 decision tree (CDT), parallel random forest (parRF), and eXtreme Gradient Boosting (XGB). …”
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    Near-infrared spectroscopy for early selection of waxy cassava clones via seed analysis
  14. 36854
    “…This study proposed a framework using five machine learning (ML) predictive algorithms—random forest, stochastic gradient boosting, least absolute shrinkage and selection operator regression, ridge regression, and extreme gradient boosting—to identify the major risk factors affecting male sperm count based on a major health screening database in Taiwan. …”
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    Machine Learning Predictive Models for Evaluating Risk Factors Affecting Sperm Count: Predictions Based on Health Screening Indicators
  15. 36855
    “…LASSO regression and random forest algorithms were then used to screen the key NFRGs. …”
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    Identification and validation of neurotrophic factor-related gene signatures in glioblastoma and Parkinson’s disease
  16. 36856
    “…Support vector regression, random forest regression, and k-nearest neighbor regression (KNR) Sc prediction models were constructed, which were based on single and combined variables. …”
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    Estimating stomatal conductance of citrus under water stress based on multispectral imagery and machine learning methods
  17. 36857
    “…The discriminatory accuracy of identified VOCs was assessed using subject work characterization and a random forest risk prediction model. (3) Results: the proposed technique has good performance compared with existing approaches, the differences between the exhaled VOCs of the early lung cancer patients before operation, three to seven days after the operation, as well as four to six weeks after operation under fasting and 1 h after the meal were compared with the healthy controls. …”
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    LC-MS/MS Based Volatile Organic Compound Biomarkers Analysis for Early Detection of Lung Cancer
  18. 36858
    “…Of machine learning models tested, the gradient-boosted tree model gave global optimal results, with the Youden index of J = 0.7, sens = 0.89, and spc = 0.81 achieved for the given set of conditions. Random forest models also performed well, achieving J > 0.63, with sens = 0.83 and spc = 0.81. …”
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    Diagnostic Screening of Bovine Mastitis Using MALDI-TOF MS Direct-Spotting of Milk and Machine Learning
  19. 36859
    “…The serum metabolic profiles were compared using various multivariate statistical analysis tools available on MetaboAnalyst (freely available web-based software) such as partial least-squares discriminant analysis (PLS-DA) and random forest (a machine learning) classification method. …”
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    Nuclear Magnetic Resonance-Based Metabolomics Approach Revealed the Intervention Effect of Using Complementary and Alternative Medicine (CAM) by CKD Patients
  20. 36860
    “…Thereafter, multivariate models like support vector machine regression (SVM), partial least squares (PLS), random forest (RF), and multivariate adaptive regression spline (MARS) were also used to estimate blast severity. …”
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    Spectral characterization and severity assessment of rice blast disease using univariate and multivariate models
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