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  1. 36241
    “…They are a diverse group of 225 species and 45 genera and occur in lowlands and lower montane forests of Neotropics. Despite the large degree of diversity seen in this family, just four species of Thamnophilidae have been karyotyped with a diploid number ranging from 76 to 82 chromosomes. …”
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    Analysis of multiple chromosomal rearrangements in the genome of Willisornis vidua using BAC-FISH and chromosome painting on a supposed conserved karyotype
  2. 36242
    “…Four machine-learning-based prediction models were established and compared, including the K-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), and logistic regression (LR) algorithms. …”
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    A prediction model based on DNA methylation biomarkers and radiological characteristics for identifying malignant from benign pulmonary nodules
  3. 36243
    “…Several machine learning algorithms (random forest, XGBoost, naïve Bayes, and logistic regression) were used to assess the 3-year risk of developing cognitive impairment. …”
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    A Risk Prediction Model Based on Machine Learning for Cognitive Impairment Among Chinese Community-Dwelling Elderly People With Normal Cognition: Development and Validation Study
  4. 36244
    “…To examine the reproducibility of protein-mortality associations we used a two-step random-split approach to simulate a discovery and replication cohort and conducted analyses using four different methods: Cox regression, stepwise Cox regression, Lasso-Cox regression, and random survival forest (RSF). In the total study population, we identified eight proteins that associated with all-cause mortality after adjustment for established risk factors and with Bonferroni correction for multiple testing. …”
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    Methodological considerations for identifying multiple plasma proteins associated with all-cause mortality in a population-based prospective cohort
  5. 36245
    “…It was based on this that we investigated the Baka community of Abong-Mbang Health District in tropical rain forest of Cameroon. METHODS: A cross-sectional study was conducted with participants randomly selected from 13 villages in Abong-Mbang by multi-stage cluster sampling. …”
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    Assessing the determinants of Ebola virus disease transmission in Baka Community of the Tropical Rainforest of Cameroon
  6. 36246
    “…Meanwhile, we used traditional regression analysis (univariate Cox analysis, random survival forest analysis, and lasso regression analysis) to screen the cancer-related lncRNAs. …”
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    Comprehensive analyses of correlation and survival reveal informative lncRNA prognostic signatures in colon cancer
  7. 36247
    “…The heterogeneity of studies was assessed using the Cochrane Q test statistic, I(2) test statistic, and, visually, using Forest and Galbraith’s plots. A random-effect model was applied to get the pooled birth prevalence of neural tube defects. …”
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    Birth prevalence of neural tube defects and associated risk factors in Africa: a systematic review and meta-analysis
  8. 36248
    “…A meta-analysis was performed, and forest plots were drawn. Results: We included 23 studies which all revealed that patients in DHI groups had better efficacy than control groups. …”
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    Comparison of the Efficacy of Danhong Injections at Different Time-points During the Perioperative Period of Acute Myocardial Infarction: A Systematic Review and Meta-analysis of Randomized Controlled Trials
  9. 36249
    “…We also constructed a risk prediction model using the random survival forest method to analyze right-censored survival data based on key metabolic genes. …”
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    Metabolic classification of bladder cancer based on multi-omics integrated analysis to predict patient prognosis and treatment response
  10. 36250
    “…Accelerometer data from each body position and combinations of positions were used to develop random forest models to assess activity category recognition accuracy and MET estimation. …”
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    The Effect of Sensor Placement and Number on Physical Activity Recognition and Energy Expenditure Estimation in Older Adults: Validation Study
  11. 36251
    “…We compared extreme gradient boosting, random forest, neural networks, and C5.0 decision tree for automated health information understandability evaluation. …”
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    Use of Machine Learning Algorithms to Predict the Understandability of Health Education Materials: Development and Evaluation Study
  12. 36252
    “…For group classification, 4 classifiers were used and compared, those being [Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naive Bayes (NB)]. …”
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    Discrimination between healthy and patients with Parkinson’s disease from hand resting activity using inertial measurement unit
  13. 36253
    por Back, Georg, Walther, Dirk
    Publicado 2021
    “…To identify additional IME-related genomic features, Random Forest models were trained for the classification of gene expression level based on an array of sequence-related features. …”
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    Identification of cis-regulatory motifs in first introns and the prediction of intron-mediated enhancement of gene expression in Arabidopsis thaliana
  14. 36254
    “…Here, we used genome-wide single nucleotide polymorphism (SNP) data on 806 individuals belonging to 36 breeds to reconstruct the origin and diversification of Podolian cattle and to provide a reliable scenario of the European colonization, through an approximate Bayesian computation random forest (ABC-RF) approach. RESULTS: Our results indicate that European Podolian cattle display higher values of genetic diversity indices than both African taurine and Asian indicine breeds. …”
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    On the origin and diversification of Podolian cattle breeds: testing scenarios of European colonization using genome-wide SNP data
  15. 36255
    “…We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and used these bacterial profiles to classify SARS-CoV-2 RNA detection with a random forest model. RESULTS: Sixteen percent of surfaces from COVID-19 patient rooms had detectable SARS-CoV-2 RNA, although infectivity was not assessed. …”
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    SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment
  16. 36256
    “…Logistic regression, support vector machine (SVM), deep neural network (DNN), random forest, and decision tree models were evaluated to generate a robust prediction model. …”
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    Predictors of 30-Day Unplanned Readmission After Carotid Artery Stenting Using Artificial Intelligence
  17. 36257
    “…The results were compared using logistic regression, random forest (RF) and support vector machine (SVM) models from the same dataset. …”
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    Patient similarity analytics for explainable clinical risk prediction
  18. 36258
    “…Merging the three datasets allowed considering FCR values (Mean = 2.85; Min = 1.92; Max = 5.00) for a total of n = 148 pigs, with a large range of body weight (15 to 115 kg) and different test period duration (2 to 9 weeks). Random forest (RF) and gradient tree boosting (GTB) were applied on the whole blood transcripts (26,687 annotated molecular probes) to identify the most important variables for binary classification on RFI groups and a quantitative prediction of FCR, respectively. …”
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    Analysis of merged whole blood transcriptomic datasets to identify circulating molecular biomarkers of feed efficiency in growing pigs
  19. 36259
    “…Among the machine learning methods, generalized boosting machines using the Poisson distribution as well as random forests regression were the best performing. No model was able to capture the bucket shaped hometime distribution and future research on factors which are associated with extreme values of hometime that are not available in administrative data is warranted. …”
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    Comparing regression modeling strategies for predicting hometime
  20. 36260
    “…Higher IgG levels were associated with older age (>18 years, p < 0.05) and males (17/23 proteins, p < 0.05), supporting the paradigm that men have a higher risk of infection than females in this setting. We used a Random Forests algorithm to predict which individuals had exposure to P. vivax parasites in the last 9-months, based on their IgG antibody levels to a panel of eight previously validated P. vivax proteins. …”
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    Application of 23 Novel Serological Markers for Identifying Recent Exposure to Plasmodium vivax Parasites in an Endemic Population of Western Thailand
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