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  1. 37081
    “…Machine learning algorithms, i.e. missForest and k-NN, were also found to lack robustness to small changes in the data or consecutive missingness. …”
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    Addressing missing values in routine health information system data: an evaluation of imputation methods using data from the Democratic Republic of the Congo during the COVID-19 pandemic
  2. 37082
    “…Strict regulations of the health-threatening pesticide by the regulatory body (Environment, Forest and Climate Change Commission) at the country and regional levels is advocated.…”
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    Exposure of infants to organochlorine pesticides from breast milk consumption in southwestern Ethiopia
  3. 37083
    “…For each combination (SECT/DECT and patient response/lesion response), an individual random forest classifier with 10-fold internal cross-validation was trained on the study cohort and tested on the validation cohort to confirm the predictive performance. …”
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    A Machine learning model trained on dual-energy CT radiomics significantly improves immunotherapy response prediction for patients with stage IV melanoma
  4. 37084
    “…Mean difference (MD) with 95% CI was used to quantify the change in ARR and change in EDSS before and after treatment. A forest plot was prepared to indicate the efficacy and adverse effects outcomes. …”
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    Safety and efficacy of interleukin-6-receptor inhibitors in the treatment of neuromyelitis optica spectrum disorders: a meta-analysis
  5. 37085
    “…Effect sizes of outcome for each group were pooled using random-effects models; thereafter, the results were represented in the forest plots. RESULTS: Nine RCTs with 293 EM and 303 LM participants were identified and included in the study. …”
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    In adults, early mobilization may be beneficial for distal radius fractures treated with open reduction and internal fixation: a systematic review and meta-analysis
  6. 37086
    “…These pangolins had been admitted to a regional Wildlife Quarantine Center for rehabilitation before release in the forest. Routine physical examinations were conducted on the animals. …”
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    First report on detection of Babesia spp. in confiscated Sunda pangolins (Manis javanica) in Thailand
  7. 37087
    “…Finally, we assessed the spatio-temporal concordance of fox digging and greater snow goose (Anser caerulescens antlanticus) nesting, to test the ecological relevance of our behavioural classification in a well-known study system dominated by top-down trophic interactions. RESULTS: The random forest model yielded the best behavioural classification, with accuracies for each behaviour over 96%. …”
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    Digging into the behaviour of an active hunting predator: arctic fox prey caching events revealed by accelerometry
  8. 37088
    “…Prediction models were built using decision tree (DT), random forest (RF), support vector machine (SVM), and LR, and their performances were evaluated using parameters of confusion matrix, receiver operating characteristics (ROC) curves, and k-fold cross-validation techniques. …”
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    Prevalence and predicting factors of perceived stress among Bangladeshi university students using machine learning algorithms
  9. 37089
    “…Using 10-fold and group k-fold cross-validation, XG-Boost and Random Forest based regression models were trained on the features derived from the hyperspectral data corresponding to each sepal in the training set and tested on hold out test set. …”
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    Predicting sensitivity of recently harvested tomatoes and tomato sepals to future fungal infections
  10. 37090
    “…STATISTICAL METHOD: Risk-prediction models were developed using randomForest then externally validated. RESULTS: Area under the receiver operating characteristic curve (AUC(ROC)) of the final model was 80.8% (95% CI 80.0% to 81.6%), sensitivity 80.3% (77.7% to 82.9%), specificity 69.1% (68.7% to 69.5%), positive predictive value (PPV) 11.1% (10.3% to 11.9%) and negative predictive value (NPV) 98.7% (98.5% to 98.9%). …”
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    Ten-year prediction model for post-bronchodilator airflow obstruction and early detection of COPD: development and validation in two middle-aged population-based cohorts
  11. 37091
    “…Several fungal Amplicon Sequence Variants (ASVs), reported as GTD-associated pathogens like Kalmusia variispora, Fomitiporia spp., and Phaemoniella chlamydosporα (most dominant in our study), were positively correlated with symptomatic vines in a cultivar/viticultural zone dependent manner. Random Forest analysis pointed to P. chlamydosporα, K. variispora, A. alternata and Cladosporium sp., as highly accurate predictors of symptomatic vines (0% error rate). …”
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    Grapevine wood microbiome analysis identifies key fungal pathogens and potential interactions with the bacterial community implicated in grapevine trunk disease appearance
  12. 37092
    “…In smoke from tropical C3 dry forest fires in Senegal, δ(13)C(CH(4)) values were around −28‰. …”
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    Isotopic signatures of methane emissions from tropical fires, agriculture and wetlands: the MOYA and ZWAMPS flights
  13. 37093
    “…This study aims to apply different machine learning (ML) techniques, specifically, random forest (RF), functional network (FN), and adaptive neuro-fuzzy inference system (ANFIS), to predict the σ(h) and σ(H) using well-log data. …”
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    Machine learning application to predict in-situ stresses from logging data
  14. 37094
    “…T2WI- and ADC-derived delta-radiomics features were computed using baseline and latest available MRI scans, with the predictive modelling performed using the parenclitic networks (PN), least absolute shrinkage and selection operator (LASSO) logistic regression, and random forests (RF) algorithms. Standard measures of discrimination and areas under the ROC curve (AUCs) were calculated, with AUCs compared using DeLong’s test. …”
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    Comparative performance of MRI-derived PRECISE scores and delta-radiomics models for the prediction of prostate cancer progression in patients on active surveillance
  15. 37095
    “…Extreme gradient boosting, which was selected as the final model, accomplished an average area under the receiver operating characteristic curve score that was 0.865 higher than that of the other models (ie, logistic regression, random forest, support vector machine, and multilayer perceptron). …”
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    Machine Learning–Based Hospital Discharge Prediction for Patients With Cardiovascular Diseases: Development and Usability Study
  16. 37096
    “…Where connected habitat with high forest cover was scarce the animals moved more directly than when habitat was abundant. …”
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    Movement and dispersal of a habitat specialist in human-dominated landscapes: a case study of the red panda
  17. 37097
    “…We developed four machine learning models [logistic regression (LR), regularized LR (RLR), support vector machine (SVM), and random forest (RF)], whose performance was internally validated using 5-fold cross-validation. …”
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    Machine Learning-Based Model for Predicting Incidence and Severity of Acute Ischemic Stroke in Anterior Circulation Large Vessel Occlusion
  18. 37098
    “…Four donor/recipient pair groups (DRP) were studied, AA/AA, AA/EA, EA/AA, and EA/EA. Survival random forests and Cox proportional hazard models were fitted to rank and evaluate modifying effects of DRP on variables associated with allograft survival. …”
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    Employment status at transplant influences ethnic disparities in outcomes after deceased donor kidney transplantation
  19. 37099
    “…The performance of different antithrombotic regimens in terms of long-term clinical outcomes and bioprosthesis valve function requires further investigation. GRAPHIC ABSTRACT: Forest plots from pairwise and network meta-analyses associated with an antithrombotic therapy with or without clopidogrel Risk ratio for all outcomes of interest calculated with the pairwise meta-analysis (left side) and for main outcomes calculated with the network meta-analysis (right side) in patients allocated to an antithrombotic therapy with clopidogrel or without. …”
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    Antithrombotic therapy with or without clopidogrel after transcatheter aortic valve replacement. A meta-analysis of randomized controlled trials
  20. 37100
    “…Trained classifiers included classification trees, LASSO-regularized logistic regression, boosted trees, and random forests. Final performance measures were reported on the training set using leave-one-out cross validation and validated on held-out samples. …”
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    Germline biomarkers predict toxicity to anti-PD1/PDL1 checkpoint therapy
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