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  1. 36721
    “…Taub (Mimosaceae) is a large tree native to dry tropical Africa and characteristic of dry leguminous forests. Different parts of this plant are used to treat wounds, skin infection, and to fight against cancer. …”
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    Online Artículo Texto
    Antibacterial and Antioxidant Activities of Isolated Compounds from Prosopis africana Leaves
  2. 36722
    “…Our ozone forecasting system consists of two ML models, ML1 and ML2, to improve predictability: ML1 uses the random forest (RF) classifier and multiple linear regression (MLR) models, and ML2 uses a two-phase RF regression model with best-fit weighting factors. …”
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    Development of a Machine Learning Approach for Local-Scale Ozone Forecasting: Application to Kennewick, WA
  3. 36723
    “…The two machine learning algorithms were Neural Network Autoregression (NNAR) and Random Forest (RF). A hybrid model combining the statistical and algorithmic approaches (ARIMA-Boosted) was also explored. …”
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    Forecasting SARS-CoV-2 Incidence in Ontario Municipalities with Statistical and Algorithmic Modeling and Ensembles
  4. 36724
    “…The ML model was built based on a development set (70%) using logistic regression, random forest (RF), and support vector machine (SVM) analyses and assessed in a validation set (30%). …”
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    Machine Learning Model to Stratify the Risk of Lymph Node Metastasis for Early Gastric Cancer: A Single-Center Cohort Study
  5. 36725
    “…We also included in the analysis PM(2.5), PM(10) and NO(2) population weighted exposure (PWE) values obtained using a four-stage approach based on the machine learning method, “random forest”, which uses space–time predictors, satellite data, and air quality monitoring data estimated at the national level. …”
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    A Methodological Approach to Use Contextual Factors for Epidemiological Studies on Chronic Exposure to Air Pollution and COVID-19 in Italy
  6. 36726
    “…Nomograms estimating OS and early recurrence were constructed using multivariate Cox regression analysis, based on the random survival forest (RSF) model. We evaluated the discrimination and calibration abilities of the nomograms using concordance indices (C-index), calibration curves, and Kaplan‒Meier curves. …”
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    Nomograms for Predicting Hepatocellular Carcinoma Recurrence and Overall Postoperative Patient Survival
  7. 36727
    “…Isolation of L. monocytogenes from various rural and urban environments showed higher prevalence in agricultural and urban developments than in forest or mountain areas, and that detection was positively associated with rainfall. …”
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    Whole-Genome Sequencing Analysis of Listeria monocytogenes from Rural, Urban, and Farm Environments in Norway: Genetic Diversity, Persistence, and Relation to Clinical and Food Isolates
  8. 36728
    “…Then, a two-step machine learning approach combining Random Forest (RF) and XGBoost (candidates were first selected by RF and further assessed by XGBoost) was performed, which identified 44 circRNAs and 39 miRNAs as potential biomarkers (i.e., novel_circ_0000180, novel_circ_0000365, novel_miR_192, oar-miR-496-3p) for E. coli infection. …”
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    Non-Coding Transcriptome Provides Novel Insights into the Escherichia coli F17 Susceptibility of Sheep Lamb
  9. 36729
    “…ABSTRACT: Ambrosia beetles bore into the xylem of woody plants, reduce timber quality, and can sometimes cause devastating damage to forest ecosystems. The colonization by different beetle species is dependent on host status, from healthy trees to the early stages of wood decay, although the precise factors influencing their host selection are not well known. …”
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    Succession of Ambrosia Beetles Colonizing the Logs of Fallen Alder and Birch Trees
  10. 36730
    “…RESULTS: Using one half of the data as a discovery set (69 disease cases and 69 control cases), the elastic net feature selection and random forest classifier assembly were used in cross-validation to identify a 15-transition classifier. …”
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    A Plasma-Based Protein Marker Panel for Colorectal Cancer Detection Identified by Multiplex Targeted Mass Spectrometry
  11. 36731
    “…Differentially expressed genes (DEGs) were selected between platinum-sensitive and platinum-resistant patients from the training cohort, and multiple machine-learning algorithms [including random forest, XGboost, and least absolute shrinkage and selection operator (LASSO) regression] were utilized to determine the candidate genes from DEGs. …”
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    Establish of an Initial Platinum-Resistance Predictor in High-Grade Serous Ovarian Cancer Patients Regardless of Homologous Recombination Deficiency Status
  12. 36732
    “…Analysis was performed using machine learning methods, including random forest and factor analysis, to prioritize the numbers of genes from previous SCZ studies. …”
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    Expansion of Schizophrenia Gene Network Knowledge Using Machine Learning Selected Signals From Dorsolateral Prefrontal Cortex and Amygdala RNA-seq Data
  13. 36733
    por Zhao, Huan, Guo, Qiang, Li, Baoli, Shi, Min
    Publicado 2022
    “…RevMan 5.3 software was applied to analyze the data and generate the forest plot and funnel plot. Meanwhile, publication bias was also assessed by Egger’s test with STATA 12 software. …”
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    The Efficacy and Safety of Ginkgo Terpene Lactone Preparations in the Treatment of Ischemic Stroke: A Systematic Review and Meta-Analysis of Randomized Clinical Trials
  14. 36734
    “…Four machine learning algorithms (gradient boosting machine, support vector machine, logistic regression, and random forest (RF)) were used to identify the critical clinical and pathological features and to build a risk prediction model for ESRD. …”
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    Development and internal validation of machine learning algorithms for end-stage renal disease risk prediction model of people with type 2 diabetes mellitus and diabetic kidney disease
  15. 36735
    “…In addition, there exists a strongly positive relation between GA, short-chain fatty acid (SCFA) or other prebiotics, and those commensals using random forest machine learning algorithm and Spearman correlation analyses. …”
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    Protective Effects of Intestinal Gallic Acid in Neonatal Dairy Calves Against Extended-Spectrum β-lactamase Producing Enteroaggregative Escherichia coli Infection: Modulating Intestinal Homeostasis and Colitis
  16. 36736
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    Reconstructing an historical pollination syndrome: keel flowers
  17. 36737
    “…We applied six common ML-based classifiers: decision tree (DT), random forest (RF), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), logistic regression (LR), and linear discriminant analysis (LDA) to predict hypertension and its risk factors. …”
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    Machine Learning Approaches for Predicting Hypertension and Its Associated Factors Using Population-Level Data From Three South Asian Countries
  18. 36738
    “…We investigated potential prognostic factors via Cox proportional hazards model and Kaplan–Meier estimator. Nomogram model and forest plot were constructed to illustrate the prognostic value of age. …”
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    Prognostic Effect of Age in Resected Pancreatic Cancer Patients: A Propensity Score Matching Analysis
  19. 36739
    “…The predicted daily number of ACS has been estimated with the Random Forest machine learning system based on air temperature (°C), air pressure (hPa), dew point temperature (Td) (°C), relative humidity (RH) (%), wind speed (m/s), and precipitation (mm) and their daily extremes and ranges derived from the day of ACS and from 6 days before ACS. …”
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    Machine Learning Analyzed Weather Conditions as an Effective Means in the Predicting of Acute Coronary Syndrome Prevalence
  20. 36740
    “…We developed methods to estimate postoperative CRC risk based on the gut microbiome and metabolomic compositions using a random forest machine-learning algorithm that classifies large adenoma or early-stage CRC and healthy controls from publicly available data sets. …”
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    Surgical Treatment for Colorectal Cancer Partially Restores Gut Microbiome and Metabolome Traits
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